CRAN Package Check Results for Package stremr

Last updated on 2018-04-16 13:47:40 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.4 23.07 189.74 212.81 ERROR
r-devel-linux-x86_64-debian-gcc 0.4 17.12 144.88 162.00 ERROR
r-devel-linux-x86_64-fedora-clang 0.4 268.84 ERROR
r-devel-linux-x86_64-fedora-gcc 0.4 262.55 ERROR
r-devel-windows-ix86+x86_64 0.4 50.00 497.00 547.00 OK
r-devel-osx-x86_64 0.4 ERROR
r-patched-linux-x86_64 0.4 19.84 193.30 213.14 ERROR
r-patched-solaris-x86 0.4 376.00 ERROR
r-release-linux-x86_64 0.4 13.93 201.08 215.01 ERROR
r-release-windows-ix86+x86_64 0.4 38.00 493.00 531.00 OK
r-release-osx-x86_64 0.4 ERROR
r-oldrel-windows-ix86+x86_64 0.4 26.00 410.00 436.00 OK

Check Details

Version: 0.4
Check: compiled code
Result: NOTE
    File ‘stremr/libs/stremr.so’:
     Found no calls to: ‘R_registerRoutines’, ‘R_useDynamicSymbols’
    
    It is good practice to register native routines and to disable symbol
    search.
    
    See ‘Writing portable packages’ in the ‘Writing R Extensions’ manual.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 0.4
Check: tests
Result: ERROR
     Running ‘test-all.R’ [129s/172s]
    Running the tests in ‘tests/test-all.R’ failed.
    Complete output:
     > ## unit tests will not be done if RUnit is not available
     > # setwd("..")
     > # getwd()
     > # library(RUnit)
     > if(require("RUnit", quietly=TRUE)) {
     + ## --- Setup ---
     +
     + pkg <- "stremr" # <-- Tested package name
     +
     + if(Sys.getenv("RCMDCHECK") == "FALSE") {
     + ## Path to unit tests for standalone running under Makefile (not R CMD check)
     + ## PKG/tests/../inst/unitTests
     + # path <- file.path(getwd(), "..", "inst", "unitTests")
     + } else {
     + ## Path to unit tests for R CMD check
     + ## PKG.Rcheck/tests/../PKG/unitTests
     + # path <- system.file(package=pkg, "RUnit")
     +
     + # REPLACED WITH:
     + path <- file.path(getwd(), "RUnit")
     + }
     +
     + cat("\nRunning unit tests\n")
     + print(list(pkg=pkg, getwd=getwd(), pathToUnitTests=path))
     +
     + library(package=pkg, character.only=TRUE)
     +
     + ## If desired, load the name space to allow testing of private functions
     + ## if (is.element(pkg, loadedNamespaces()))
     + ## attach(loadNamespace(pkg), name=paste("namespace", pkg, sep=":"), pos=3)
     + ##
     + ## or simply call PKG:::myPrivateFunction() in tests
     +
     + ## --- Testing ---
     +
     + ## Define tests
     + test.suite <- defineTestSuite(name=paste(pkg, "unit testing"),
     + # dirs="./RUnit",
     + dirs=path,
     + testFileRegexp = "^RUnit_tests_+",
     + testFuncRegexp = "^test.+",
     + rngKind = "Marsaglia-Multicarry",
     + rngNormalKind = "Kinderman-Ramage")
     + ## Run
     + tests <- runTestSuite(test.suite)
     +
     + ## Default report name
     + pathReport <- file.path(path, "report")
     +
     + ## Report to stdout and text files
     + cat("------------------- UNIT TEST SUMMARY ---------------------\n\n")
     + printTextProtocol(tests, showDetails=FALSE)
     + printTextProtocol(tests, showDetails=FALSE,
     + fileName=paste0(pathReport, "Summary.txt"))
     + printTextProtocol(tests, showDetails=TRUE,
     + fileName=paste0(pathReport, ".txt"))
     + ## Report to HTML file
     + printHTMLProtocol(tests, fileName=paste0(pathReport, ".html"))
     +
     + ## Return stop() to cause R CMD check stop in case of
     + ## - failures i.e. FALSE to unit tests or
     + ## - errors i.e. R errors
     + tmp <- getErrors(tests)
     + if(tmp$nFail > 0 | tmp$nErr > 0) {
     + stop(paste("\n\nunit testing failed (#test failures: ", tmp$nFail,
     + ", #R errors: ", tmp$nErr, ")\n\n", sep=""))
     + }
     + } else {
     + warning("cannot run unit tests -- package RUnit is not available")
     + }
    
     Running unit tests
     $pkg
     [1] "stremr"
    
     $getwd
     [1] "/home/hornik/tmp/R.check/r-devel-clang/Work/PKGS/stremr.Rcheck/tests"
    
     $pathToUnitTests
     [1] "/home/hornik/tmp/R.check/r-devel-clang/Work/PKGS/stremr.Rcheck/tests/RUnit"
    
    
    
     Executing test function test.GenericModelPredict ... Loading required package: data.table
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.6829138 1.4512950 -0.4353432 0.5852046
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "catA"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: catA"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA, catA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "CategorModel outcome: catA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA_B.1, catA_B.2, catA_B.3"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "CategorModel outcome: catA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA_B.1, catA_B.2, catA_B.3"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for outcome based on stratified model for outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: catA"
     [1] "freq counts by bin for categorical outcome: "
    
     1 2 3
     4629 4747 4613
     [1] "binned dataset: "
     sA catA_B.1 catA_B.2 catA_B.3
     [1,] 1 NA 1 NA
     [2,] 3 NA 1 NA
     [3,] 3 NA 1 NA
     [4,] 1 NA 1 NA
     [5,] 3 NA 1 NA
     [1] "fitting the model: P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     [1] "fitting the model: P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -9.762950e-08 2.155173e-06 NA
     [1] "fitting the model: P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for catA var succeeded...
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: catA"
     [1] "freq counts by bin for categorical outcome: "
    
     1 2 3
     4629 4747 4613
     [1] "binned dataset: "
     sA catA_B.1 catA_B.2 catA_B.3
     [1,] 1 NA 1 NA
     [2,] 3 NA 1 NA
     [3,] 3 NA 1 NA
     [4,] 1 NA 1 NA
     [5,] 3 NA 1 NA
     [1] "fitting the model: P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     [1] "fitting the model: P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -3.738646e-08 -2.346217e-07 -2.013073e-07
     [1] "fitting the model: P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for catA var succeeded...
     fit for catA var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: catA"
     [1] "performing prediction for categorical outcome: catA"
     [1] "performing prediction for categorical outcome: catA"
     [1] "performing prediction for outcome based on stratified model: catA"
     [1] "performing prediction for categorical outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing prediction for categorical outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     done successfully.
    
    
    
     Executing test function test.Nsamp.n.test ... done successfully.
    
    
    
     Executing test function test.options ... [1] "Possible `stremr` options:"
     [1] "fit.package" "fit.algorithm" "bin.method"
     [4] "nbins" "maxncats" "maxNperBin"
     [7] "lower_bound_zero_Q" "skip_update_zero_Q"
     Error in stremrOptions("blahblah") :
     blahblah: this options does not exist
     Error in stremrOptions("blahblah", 5) : Invalid option name: blahblah
     Error in if (!(fit.algorithm %in% allowed.fit.algorithm)) stop("fit.algorithm must be one of: " %+% :
     argument is of length zero
     Error in set_all_stremr_options(fit.package = "speedglm", fit.algorithm = "blahblah", :
     fit.algorithm must be one of: glm, gbm, randomForest, deeplearning
     Error in set_all_stremr_options(fit.package = "blahblah", fit.algorithm = "glm", :
     fit.package must be one of: speedglm, glm, h2o
     Error in set_all_stremr_options(fit.package = "speedglm", fit.algorithm = "glm", :
     bin.method must be one of: equal.mass, equal.len, dhist
     $fit.package
     [1] "speedglm"
    
     $fit.algorithm
     [1] "glm"
    
     $bin.method
     [1] "equal.mass"
    
     $nbins
     [1] 10
    
     $maxncats
     [1] 20
    
     $maxNperBin
     [1] 500
    
     $lower_bound_zero_Q
     [1] TRUE
    
     $skip_update_zero_Q
     [1] TRUE
    
     done successfully.
    
    
    
     Executing test function test.regressionCases ... done successfully.
    
    
    
     Executing test function test.t.error ... done successfully.
    
    
    
     Executing test function test.DataStorageClass ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     Error in OData$get.outvar(var = "blah") :
     requested variable blah does not exist in DataStorageClass!
     done successfully.
    
    
    
     Executing test function test.error.fits.stratify ... Error in create_subset_expr(outvars = res$outvars, stratify.EXPRS = stratify.EXPRS) :
     Could not locate the appropriate regression variable(s) within the supplied stratification list stratify_CENS, stratify_TRT or stratify_MONITOR.
     The regression outcome variable(s) specified in gform_CENS, gform_TRT or gform_MONITOR were: ( 'C,TI' )
     However, the item names in the matching stratification list were: ( 'wrongC,TI,N' )
     done successfully.
    
    
    
     Executing test function test.helperfuns ... done successfully.
    
    
    
     Executing test function test.model.fits.stratify ... done successfully.
    
    
    
     Executing test function test.model.fits.categorCENSOR ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.52652066 0.05456581 0.10858685
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.19067146 NA 0.43343872 -0.01789425
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01340964 NA NA -0.03245807 -0.01185101
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 8.599825e-13 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.29183433 -0.07998923 0.03081559
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.64534186 NA 0.09366241 -0.16923766
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01135495 NA NA -0.02269938 -0.01321850
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 1,t > 0 & C == 1)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 1"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 1"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 1 & TI == 1,t > 0 & C == 1 & TI == 1)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 1 & TI == 1"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 1 & TI == 1"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 8.599825e-13 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.29183433 -0.07998923 0.03081559
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     NA NA NA NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     NA 0.4924641 0.1270091 -0.1911502
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 1 & TI == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     NA NA NA NA NA
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 1 & TI == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     NA NA NA NA NA
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,t > 0L & TI.tminus1 == 0L,t > 0L & TI.tminus1 == 1L)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 1L"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.52652066 0.05456581 0.10858685
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.64534186 NA 0.09366241 -0.16923766
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     -0.01467019 -0.45533330 NA NA NA
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     -0.01135495 -0.02269938 -0.01321850 NA NA
     fit for N var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -21.2548627 0.9100488 2.1714524 19.1407169
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 1L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 1.092843e-07 1.158713e-07 1.320318e-07
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "performing prediction for outcome based on stratified model: TI"
     done successfully.
    
    
    
     Executing test function test.model.fits.categorCENSOR2 ... Loading required package: magrittr
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "CatC"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: CatC"
     [1] "StratifiedModel expressions: (t < 16,t == 16)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC, CatC"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     ...fitting a model for categorical censoring...
     [1] "CategorModel outcome: CatC"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC_B.1, CatC_B.2, CatC_B.3"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.1|highA1c);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.2|highA1c);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.3|highA1c);\\ Stratify: t < 16"
     ...fitting a model for categorical censoring...
     [1] "CategorModel outcome: CatC"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC_B.1, CatC_B.2, CatC_B.3"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.1|highA1c);\\ Stratify: t == 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.2|highA1c);\\ Stratify: t == 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.3|highA1c);\\ Stratify: t == 16"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,(t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L),(t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L),(t > 0L) & (barTIm1eq0 == 1L))"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI, TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L)"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L)"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (barTIm1eq0 == 1L)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: CatC"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: CatC"
     [1] "freq counts by bin for categorical outcome: "
    
     0 1 2
     7469 347 314
     [1] "binned dataset: "
     sA CatC_B.1 CatC_B.2 CatC_B.3
     [1,] 0 0 0 NA
     [2,] 0 0 0 NA
     [3,] 1 1 NA NA
     [4,] 0 0 0 NA
     [5,] 0 0 0 NA
     [1] "fitting the model: P(CatC_B.1|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -3.1487960 0.1616531
     [1] "fitting the model: P(CatC_B.2|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -3.13719779 -0.08098814
     [1] "fitting the model: P(CatC_B.3|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     NA NA
     fit for CatC var succeeded...
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: CatC"
     [1] "freq counts by bin for categorical outcome: "
    
     0 1 2
     7469 347 314
     [1] "binned dataset: "
     sA CatC_B.1 CatC_B.2 CatC_B.3
     [1,] 0 0 0 NA
     [2,] 0 0 0 NA
     [3,] 1 1 NA NA
     [4,] 0 0 0 NA
     [5,] 0 0 0 NA
     [1] "fitting the model: P(CatC_B.1|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -2.9593646 0.5614693
     [1] "fitting the model: P(CatC_B.2|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -4.89784 -15.66823
     [1] "fitting the model: P(CatC_B.3|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     NA NA
     fit for CatC var succeeded...
     fit for CatC var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.1141458 0.9100488 2.1714524 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.656607e+01 2.444839e-12 2.082888e-12 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -21.2548627 0.9100488 2.1714524 19.1407169
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: CatC"
     [1] "performing prediction for categorical outcome: CatC"
     [1] "performing prediction for categorical outcome: CatC"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "N"
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     done successfully.
    
    
    
     Executing test function test.buildingblocks ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     Error in getIPWeights(OData = OData, intervened_TRT = "TI.set1", rule_name = "TI1") :
     ...cannot locate propensity scores in 'OData' object - must run fitPropensity(...) prior to calling this function
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t < 16,t == 16)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 16"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t < 16"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.198768e-13 -5.125570e-14
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 16"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -6.143963e-14 -2.839781e-14
     fit for C var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "performing estimation for the following TRT/MONITOR rules found in column 'rule.name': TI0,TI1"
     [1] "periods"
     [1] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
     [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     [1] "Periods.0to0_TI0"
     [1] "Periods.1to1_TI0"
     [1] "Periods.2to2_TI0"
     [1] "Periods.3to3_TI0"
     [1] "Periods.4to4_TI0"
     [1] "Periods.5to5_TI0"
     [1] "Periods.6to6_TI0"
     [1] "Periods.7to7_TI0"
     [1] "Periods.8to11_TI0"
     [1] "Periods.12to15_TI0"
     [1] "Periods.0to0_TI1"
     [1] "Periods.1to1_TI1"
     [1] "Periods.2to2_TI1"
     [1] "Periods.3to3_TI1"
     [1] "Periods.4to4_TI1"
     [1] "Periods.5to5_TI1"
     [1] "Periods.6to6_TI1"
     [1] "Periods.7to7_TI1"
     [1] "Periods.8to11_TI1"
     [1] "Periods.12to15_TI1"
     ...fitting hazard MSM with speedglm::speedglm.wfit...
     [1] "MSM fits"
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     -5.465039e+00 -4.324378e+00 -4.012934e+00 -1.166619e+15
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     -6.871355e+14 -4.884654e+14 -6.732368e+00 -6.414551e+00
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     -2.490327e+15 -3.057464e+15 -3.089228e+00 -4.070768e+00
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     -4.097356e+00 -1.444049e+01 -3.626218e+00 -4.172158e+00
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     -5.928687e+00 -3.921940e+00 -4.645602e+00 -3.410729e+00
     ...evaluating MSM-based survival curves...
     ...evaluating SEs based on MSM hazard fit and the estimated IC...
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     9.379699e-17 2.900859e-16 7.383396e-15 7.293270e+00
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     6.561300e+01 4.445403e+02 3.220105e-14 2.800474e-14
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.030033e+02 7.899748e+02 7.913397e-18 2.865011e-18
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     7.009244e-18 4.879654e-08 1.399031e-19 7.292022e-18
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     2.532557e-18 1.471364e-17 3.615109e-16 1.717254e-15
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     9.340525e-15 3.126553e-15 1.800440e-14 3.336980e+14
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     7.563694e+14 1.183848e+15 5.560005e-15 5.426432e-15
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     1.830248e+14 5.408850e+14 4.968619e-15 3.569094e-15
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     6.622362e-15 1.000001e+00 8.253617e-17 2.682887e-15
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     3.708932e-15 2.085976e-15 9.255499e-15 3.032843e-15
     [1] "Should all be very small: "
     [1] 3.953818e-17 7.916801e-17 2.288376e-16 2.288376e-16 2.288376e-16
     [6] 2.288376e-16 2.227361e-16 2.339417e-16 2.339417e-16 2.339417e-16
     [11] 2.339417e-16 2.339417e-16 2.339417e-16 2.339417e-16 2.339417e-16
     [16] 2.339417e-16
     [1] "Should all be very small: "
     [1] 2.087237e-16 2.567391e-16 1.552191e-16 4.951408e-07 4.823035e-07
     [6] 4.749798e-07 4.737188e-07 4.645200e-07 4.601013e-07 4.557247e-07
     [11] 4.513896e-07 4.470959e-07 4.328058e-07 4.189726e-07 4.055814e-07
     [16] 3.926183e-07
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -2.240428e-13 -9.163027e-14
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "performing estimation for the following TRT/MONITOR rules found in column 'rule.name': TI0,TI1"
     [1] "periods"
     [1] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
     [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     [1] "Periods.0to0_TI0"
     [1] "Periods.1to1_TI0"
     [1] "Periods.2to2_TI0"
     [1] "Periods.3to3_TI0"
     [1] "Periods.4to4_TI0"
     [1] "Periods.5to5_TI0"
     [1] "Periods.6to6_TI0"
     [1] "Periods.7to7_TI0"
     [1] "Periods.8to11_TI0"
     [1] "Periods.12to15_TI0"
     [1] "Periods.0to0_TI1"
     [1] "Periods.1to1_TI1"
     [1] "Periods.2to2_TI1"
     [1] "Periods.3to3_TI1"
     [1] "Periods.4to4_TI1"
     [1] "Periods.5to5_TI1"
     [1] "Periods.6to6_TI1"
     [1] "Periods.7to7_TI1"
     [1] "Periods.8to11_TI1"
     [1] "Periods.12to15_TI1"
     ...fitting hazard MSM with speedglm::speedglm.wfit...
     [1] "MSM fits"
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     -5.479625e+00 -4.224521e+15 -4.040682e+15 -3.195295e+15
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     -3.082898e+15 -2.778817e+15 -3.052026e+15 -3.796228e+15
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     -2.715406e+15 -1.534193e+15 -3.048470e+00 -4.020852e+00
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     -4.106498e+00 -1.007712e+01 -3.450746e+00 -4.160778e+00
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     -5.909203e+00 -4.008647e+00 -4.781623e+00 -3.422484e+15
     ...evaluating MSM-based survival curves...
     ...evaluating SEs based on MSM hazard fit and the estimated IC...
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     1.363995e-15 3.892340e+00 1.153066e+02 3.014492e+03
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     2.096739e+04 2.100000e+04 1.300000e+04 5.000000e+03
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.700000e+04 1.000000e+04 2.218218e-17 1.992734e-17
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     1.087903e-17 1.670762e-05 2.380815e-17 8.984546e-17
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     4.050727e-18 8.676045e-17 3.446043e-04 2.159757e+02
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     2.012238e-14 5.581563e+13 7.715289e+13 2.180508e+14
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     2.367837e+14 2.874638e+14 2.419289e+14 1.178953e+14
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.980323e+14 4.949011e+14 9.314984e-15 1.161900e-14
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     3.404072e-15 1.000042e+00 9.042079e-16 3.580885e-15
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     4.712621e-16 6.766642e-16 1.571325e-04 1.801860e+14
     [1] "Should all be very small: "
     [1] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [6] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [11] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [16] 8.330934e-17
     [1] "Should all be very small: "
     [1] 3.999902e-16 2.024836e-16 2.525296e-16 3.877971e-05 3.758736e-05
     [6] 3.701017e-05 3.690999e-05 3.625173e-05 3.706763e-05 3.786745e-05
     [11] 3.865142e-05 3.941974e-05 3.941974e-05 3.941974e-05 3.941974e-05
     [16] 3.941974e-05
     Error in process_opt_wts(wts_data_used, weights, nodes) :
     input 'weights' must be a data.table with 3 columns, two of which must be named as: 'ID' and 't'.
     In addition: Warning messages:
     1: glm.fit: algorithm did not converge
     2: glm.fit: algorithm did not converge
     3: glm.fit: algorithm did not converge
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -5.8682574 0.2154351 3.3021509 0.4033691 NA 0.7501467 NA
     [1] "Surv est: 0.983758322675102"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=0: 0.01624"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -4.67474313 0.19724908 2.21184261 -0.09839186 0.76483183 0.36869687
     TI.tminus1
     -0.98759997
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.48082464 0.25283340 2.46508499 0.04786835 NA -0.43706261
     TI.tminus1
     NA
     [1] "Surv est: 0.969902221464484"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=1: 0.0301"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.8073588 -1.1071567 1.3574257 -0.4540453 0.6083749 0.3767599 -1.4726757
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7570081 -0.3346276 1.4801253 -0.3532999 0.5055449 -0.5127511 -0.6589153
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.90325161 -0.07708853 2.01607750 -0.02829320 NA -0.32644563
     TI.tminus1
     NA
     [1] "Surv est: 0.953782240282527"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=2: 0.04622"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.2729961 0.6045142 2.3185601 -1.4506484 0.4525435 -1.0902410 -1.7027505
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.45925760 -0.49121038 1.40054082 -0.35287095 0.50934192 -0.02283871
     TI.tminus1
     -1.28687470
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8442520 -0.1010111 1.5056775 -0.2372471 0.4546915 -0.4782690 -0.6244729
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.94053966 0.04857403 1.99765895 0.01058704 NA -0.32554792
     TI.tminus1
     NA
     [1] "Surv est: 0.953681572539541"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04632"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.0863662 1.4415952 1.1242617 -0.4941329 -0.1391926 -0.8298997 -0.6156850
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1883548 1.2010569 1.3144619 -0.3947993 0.1333006 -0.9913184 -0.5170650
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.11978976 0.36019767 1.14780785 -0.23837798 0.37263297 -0.05869163
     TI.tminus1
     -0.85675524
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.6602088 0.3624027 1.3288288 -0.1996436 0.3619692 -0.4185487 -0.4804042
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.757594710 0.346812991 1.758549008 0.002438552 NA -0.302239540
     TI.tminus1
     NA
     [1] "Surv est: 0.943575229684677"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.05642"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.694637 0.368584 3.290803 -0.666631 NA NA NA
     [1] "tmle update: -0.00149135496809919"
     [1] "Surv est: 0.984107401301778"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=0: 0.01589"
     [1] "...empirical mean of the estimated EIC: -3.09079900454493e-05"
     [1] "...estimated TMLE variance: 2.41999050417123e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8004930 0.9282348 0.6879804 -0.5514791 0.7438655 NA NA
     [1] "tmle update: 0.0727160966327068"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6000572 0.5722892 2.2618565 -0.7563574 NA NA NA
     [1] "tmle update: -0.0022357049164653"
     [1] "Surv est: 0.969834495012909"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=1: 0.03017"
     [1] "...empirical mean of the estimated EIC: -6.07101133764977e-05"
     [1] "...estimated TMLE variance: 6.61356670225727e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9817186 -17.2807447 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595614761723"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715771607933"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470300657529"
     [1] "Surv est: 0.951909613102674"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=2: 0.04809"
     [1] "...empirical mean of the estimated EIC: -0.00010436571628225"
     [1] "...estimated TMLE variance: 0.000251078927354862"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595625433471"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715771369513"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470300648418"
     [1] "Surv est: 0.95190961310293"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04809"
     [1] "...empirical mean of the estimated EIC: -0.000104365720571848"
     [1] "...estimated TMLE variance: 0.000251078927359577"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.209019147885717"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8958776 0.4984205 0.7750137 1.4400473 0.1142727 NA NA
     [1] "tmle update: 0.0520880449204392"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1879874 -0.3427790 0.1064457 -0.4879009 0.5164562 NA NA
     [1] "tmle update: -0.00448980897354264"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7827815 0.1202478 0.3514419 -0.6841186 0.4586810 NA NA
     [1] "tmle update: 0.0158905661689546"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.4482301 0.1976754 1.4967452 -0.5174974 NA NA NA
     [1] "tmle update: -0.00227377143477276"
     [1] "Surv est: 0.925542187707399"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.07446"
     [1] "...empirical mean of the estimated EIC: -0.000520790968265705"
     [1] "...estimated TMLE variance: 0.00803708770988044"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.0048959544125669"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715758304584"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470301977723"
     [1] "Surv est: 0.951909613112289"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04809"
     [1] "...empirical mean of the estimated EIC: -1.65538533979754e-05"
     [1] "...estimated TMLE variance: 8.3806787779791e-06"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.209019147869959"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8958776 0.4984205 0.7750137 1.4400473 0.1142727 NA NA
     [1] "tmle update: 0.0520880449202836"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1879874 -0.3427790 0.1064457 -0.4879009 0.5164562 NA NA
     [1] "tmle update: -0.00448980955099783"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7827815 0.1202478 0.3514419 -0.6841186 0.4586810 NA NA
     [1] "tmle update: 0.0158905661764066"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.4482301 0.1976754 1.4967452 -0.5174974 NA NA NA
     [1] "tmle update: -0.00227377139578826"
     [1] "Surv est: 0.925542187729508"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.07446"
     [1] "...empirical mean of the estimated EIC: -8.12433860103523e-05"
     [1] "...estimated TMLE variance: 0.00019629047768188"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: 0.00455038396959821"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5351943 -0.2698513 0.0819634 -1.1897532 1.1194722 NA NA
     [1] "tmle update: 0.00148791277372786"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.9037005 0.1316045 1.9048099 -0.7888752 NA NA NA
     [1] "tmle update: 0.0038737545211174"
     [1] "Surv est: 0.952423126954576"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04758"
     [1] "...empirical mean of the estimated EIC: -3.11352727229658e-05"
     [1] "...estimated TMLE variance: 4.05438882728483e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.0043556607594549"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -5.1065413 0.4996280 0.7537557 1.4595663 0.1268353 NA NA
     [1] "tmle update: -6.23198919478809e-11"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.365723662 -0.465839994 0.005840225 -0.509288785 0.596038204 NA
     TI.tminus1
     NA
     [1] "tmle update: -4.44506521637441e-10"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.88176714 0.08310961 0.32781298 -0.75064933 0.51647978 NA
     TI.tminus1
     NA
     [1] "tmle update: 5.99566016142493e-11"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.5397115 0.1898817 1.5664979 -0.5505100 NA NA NA
     [1] "tmle update: 0.0027933549293886"
     [1] "Surv est: 0.931389922902869"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.06861"
     [1] "...empirical mean of the estimated EIC: -3.04000131367507e-05"
     [1] "...estimated TMLE variance: 5.41527268962014e-05"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -2.240428e-13 -9.163027e-14
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -4.661343e-14 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.830025e-13 -7.964050e-14
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     1.2490429 NA -0.4673254 -0.1775312
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.03015004 NA NA 0.01124218 -0.01120127
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -4.661343e-14 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.830025e-13 -7.964050e-14
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     1.2490429 NA -0.4673254 -0.1775312
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.03015004 NA NA 0.01124218 -0.01120127
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     done successfully.
    
    
    
     Executing test function test.speedglm.allestimators10Kdata ... [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     writing report to directory: /tmp/RtmpQ2wX30
     writing related figures to report subdirectory: figure.sim.data.example.fup2
    
    
     processing file: /tmp/RtmpQ2wX30/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
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     $ results: chr "asis"
    
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     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
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     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
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     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
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     ordinary text without R code
    
     output file: /tmp/RtmpQ2wX30/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmpQ2wX30/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpQ2wX30/sim.data.example.fup2.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-devel-clang/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpQ2wX30/rmarkdown-strac333474c55.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup2.html
     writing report to directory: /tmp/RtmpQ2wX30
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpQ2wX30/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
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     label: unnamed-chunk-1 (with options)
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     output file: /tmp/RtmpQ2wX30/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmpQ2wX30/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpQ2wX30/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-devel-clang/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpQ2wX30/rmarkdown-strac3540c9e2f.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpQ2wX30
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpQ2wX30/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
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     output file: /tmp/RtmpQ2wX30/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmpQ2wX30/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpQ2wX30/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-devel-clang/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpQ2wX30/rmarkdown-strac3169d40c7.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpQ2wX30
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpQ2wX30/report-script-rmd.spin.Rmd
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     output file: /tmp/RtmpQ2wX30/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmpQ2wX30/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpQ2wX30/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-devel-clang/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpQ2wX30/rmarkdown-strac324a269fa.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpQ2wX30
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpQ2wX30/report-script-rmd.spin.Rmd
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     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
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     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /tmp/RtmpQ2wX30/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmpQ2wX30/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpQ2wX30/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-devel-clang/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpQ2wX30/rmarkdown-strac369b3c83c.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpQ2wX30
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpQ2wX30/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
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     $ echo : logi FALSE
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     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
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     $ echo : logi FALSE
     $ results: chr "asis"
    
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     output file: /tmp/RtmpQ2wX30/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmpQ2wX30/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpQ2wX30/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-devel-clang/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpQ2wX30/rmarkdown-strac3aede3a4.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpQ2wX30
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpQ2wX30/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
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     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
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     inline R code fragments
    
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     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
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     output file: /tmp/RtmpQ2wX30/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmpQ2wX30/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpQ2wX30/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-devel-clang/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpQ2wX30/rmarkdown-strac351d15129.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
    
    
     processing file: /tmp/RtmpQ2wX30/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
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     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     !!! Error: Cannot write tmp file `tmp-pdfcrop-2802.tex' (Read-only file system)!
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     inline R code fragments
    
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     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     !!! Error: Cannot write tmp file `tmp-pdfcrop-3027.tex' (Read-only file system)!
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
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     label: unnamed-chunk-17 (with options)
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     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     !!! Error: Cannot write tmp file `tmp-pdfcrop-3259.tex' (Read-only file system)!
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
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     output file: /tmp/RtmpQ2wX30/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmpQ2wX30/report-script-rmd.utf8.md --to latex --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpQ2wX30/sim.data.example.fup.tex --table-of-contents --toc-depth 2 --template /home/hornik/tmp/R.check/r-devel-clang/Work/build/Packages/rmarkdown/rmd/latex/default-1.17.0.2.tex --number-sections --highlight-style tango --latex-engine pdflatex --variable graphics=yes --variable 'geometry:margin=1in'
     You are recommended to install the tinytex package to build PDF.FALSE
     Latexmk: This is Latexmk, John Collins, 1 January 2015, version: 4.41.
     Cannot write file 'sim.data.example.fup.aux'
    
     Latexmk, John Collins, 1 January 2015. Version 4.41
     Timing stopped at: 38.58 2.058 56.22
     Error in make_report_rmd(OData, NPMSM = list(surv1, surv2), MSM = MSM.IPAW, :
     Failed to compile /tmp/RtmpQ2wX30/sim.data.example.fup.tex.
     done successfully.
    
    
    
     Executing test function test.speedglm.stochastic.TMLE.NDE.1Kdata ... done successfully.
    
    
    
     Executing test function test.GCOMP.TMLE.10Kdata ... done successfully.
    
    
    
     Executing test function test.directRegressionDefn.10Kdata ... done successfully.
    
    
    
     Executing test function test.iterTMLE.10Kdata ... done successfully.
    
    
    
     Executing test function test.ContinModel ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "continA"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: continA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "ContinModel outcome: continA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: continA_B.1, continA_B.2, continA_B.3, continA_B.4, continA_B.5, continA_B.6, continA_B.7, continA_B.8, continA_B.9, continA_B.10, continA_B.11, continA_B.12, continA_B.13, continA_B.14, continA_B.15, continA_B.16, continA_B.17, continA_B.18, continA_B.19, continA_B.20, continA_B.21, continA_B.22, continA_B.23, continA_B.24, continA_B.25, continA_B.26, continA_B.27, continA_B.28, continA_B.29"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 29"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.4|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.5|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.6|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.7|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.8|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.9|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.10|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.11|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.12|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.13|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.14|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.15|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.16|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.17|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.18|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.19|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.20|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.21|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.22|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.23|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.24|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.25|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.26|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.27|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.28|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.29|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for continuous outcome: continA"
     [1] "freq counts by bin for continuous outcome: "
    
     2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
     519 518 518 518 518 518 518 518 518 518 518 518 518 519 518 518 518 518 518 518 518 518 518 518 518
     27 28
     518 519
     [1] "binned dataset: "
     continA_B.1 continA_B.2 continA_B.3 continA_B.4 continA_B.5 continA_B.6 continA_B.7
     [1,] 18 0 0 0 0 0 0 0
     [2,] 18 0 0 0 0 0 0 0
     [3,] 7 0 0 0 0 0 0 1
     [4,] 14 0 0 0 0 0 0 0
     [5,] 24 0 0 0 0 0 0 0
     continA_B.8 continA_B.9 continA_B.10 continA_B.11 continA_B.12 continA_B.13 continA_B.14
     [1,] 0 0 0 0 0 0 0
     [2,] 0 0 0 0 0 0 0
     [3,] NA NA NA NA NA NA NA
     [4,] 0 0 0 0 0 0 1
     [5,] 0 0 0 0 0 0 0
     continA_B.15 continA_B.16 continA_B.17 continA_B.18 continA_B.19 continA_B.20 continA_B.21
     [1,] 0 0 0 1 NA NA NA
     [2,] 0 0 0 1 NA NA NA
     [3,] NA NA NA NA NA NA NA
     [4,] NA NA NA NA NA NA NA
     [5,] 0 0 0 0 0 0 0
     continA_B.22 continA_B.23 continA_B.24 continA_B.25 continA_B.26 continA_B.27 continA_B.28
     [1,] NA NA NA NA NA NA NA
     [2,] NA NA NA NA NA NA NA
     [3,] NA NA NA NA NA NA NA
     [4,] NA NA NA NA NA NA NA
     [5,] 0 0 1 NA NA NA NA
     continA_B.29
     [1,] NA
     [2,] NA
     [3,] NA
     [4,] NA
     [5,] NA
     [1] "fitting the model: P(continA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.656607e+01 -1.172459e-11 -1.310221e-11 -2.568646e-11
     [1] "fitting the model: P(continA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.269913979 0.140292582 -0.021704661 0.003019809
     [1] "fitting the model: P(continA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.18632301 -0.24228329 -0.11740841 0.02564033
     [1] "fitting the model: P(continA_B.4|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.21348006 0.07748116 -0.09494095 0.08261446
     [1] "fitting the model: P(continA_B.5|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.12710071 0.11076695 0.03372620 -0.05330529
     [1] "fitting the model: P(continA_B.6|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.07913675 -0.02704844 0.01532261 -0.02313555
     [1] "fitting the model: P(continA_B.7|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.040488174 -0.008060512 0.004056028 -0.007814941
     [1] "fitting the model: P(continA_B.8|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.03957002 -0.19152782 -0.04607934 0.13167550
     [1] "fitting the model: P(continA_B.9|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.97901839 -0.01837467 -0.01289694 0.07222523
     [1] "fitting the model: P(continA_B.10|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.92584881 -0.10012218 0.07066511 0.05818678
     [1] "fitting the model: P(continA_B.11|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.82974785 -0.06192754 0.06709028 -0.02042766
     [1] "fitting the model: P(continA_B.12|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.67225828 -0.09127462 0.03795230 -0.19362820
     [1] "fitting the model: P(continA_B.13|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.73794863 0.06535833 -0.05057088 0.05944661
     [1] "fitting the model: P(continA_B.14|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.67855383 -0.09073920 0.05491579 0.06994882
     [1] "fitting the model: P(continA_B.15|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.53557490 -0.05013956 0.13828670 -0.09784207
     [1] "fitting the model: P(continA_B.16|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.44215652 -0.03706159 0.06559142 -0.09970478
     [1] "fitting the model: P(continA_B.17|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.403196410 0.118461405 -0.029783728 -0.005593895
     [1] "fitting the model: P(continA_B.18|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.31557745 -0.40894141 -0.03066455 0.10637038
     [1] "fitting the model: P(continA_B.19|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.209784942 -0.266649669 0.208480638 -0.007743525
     [1] "fitting the model: P(continA_B.20|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.07872230 0.01757332 0.09616724 -0.04195170
     [1] "fitting the model: P(continA_B.21|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.01670141 -0.10388579 -0.02949869 0.16036731
     [1] "fitting the model: P(continA_B.22|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.81990905 0.02129512 0.05140431 0.02879315
     [1] "fitting the model: P(continA_B.23|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.586134148 0.001460216 0.004554310 -0.047263551
     [1] "fitting the model: P(continA_B.24|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.387365495 -0.140193243 0.059837555 0.009202712
     [1] "fitting the model: P(continA_B.25|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.149719318 0.294716835 0.071981048 -0.001924936
     [1] "fitting the model: P(continA_B.26|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -0.68407480 -0.02646980 0.15932856 -0.07113554
     [1] "fitting the model: P(continA_B.27|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -0.07491591 0.27125633 0.05084294 0.06210111
     [1] "fitting the model: P(continA_B.28|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -6.203700e-07 4.814361e-06 -5.748598e-08
     [1] "fitting the model: P(continA_B.29|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for outcome continA succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for continuous outcome: continA"
     [1] "performing prediction for continuous outcome: continA"
     done successfully.
    
     ------------------- UNIT TEST SUMMARY ---------------------
    
     RUNIT TEST PROTOCOL -- Fri Apr 13 10:39:16 2018
     ***********************************************
     Number of test functions: 18
     Number of errors: 1
     Number of failures: 0
    
    
     1 Test Suite :
     stremr unit testing - 18 test functions, 1 error, 0 failures
     ERROR in test.speedglm.allestimators10Kdata: Error in make_report_rmd(OData, NPMSM = list(surv1, surv2), MSM = MSM.IPAW, :
     Failed to compile /tmp/RtmpQ2wX30/sim.data.example.fup.tex.
     Error:
    
     unit testing failed (#test failures: 0, #R errors: 1)
    
     Execution halted
Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.4
Check: tests
Result: ERROR
     Running ‘test-all.R’ [97s/141s]
    Running the tests in ‘tests/test-all.R’ failed.
    Complete output:
     > ## unit tests will not be done if RUnit is not available
     > # setwd("..")
     > # getwd()
     > # library(RUnit)
     > if(require("RUnit", quietly=TRUE)) {
     + ## --- Setup ---
     +
     + pkg <- "stremr" # <-- Tested package name
     +
     + if(Sys.getenv("RCMDCHECK") == "FALSE") {
     + ## Path to unit tests for standalone running under Makefile (not R CMD check)
     + ## PKG/tests/../inst/unitTests
     + # path <- file.path(getwd(), "..", "inst", "unitTests")
     + } else {
     + ## Path to unit tests for R CMD check
     + ## PKG.Rcheck/tests/../PKG/unitTests
     + # path <- system.file(package=pkg, "RUnit")
     +
     + # REPLACED WITH:
     + path <- file.path(getwd(), "RUnit")
     + }
     +
     + cat("\nRunning unit tests\n")
     + print(list(pkg=pkg, getwd=getwd(), pathToUnitTests=path))
     +
     + library(package=pkg, character.only=TRUE)
     +
     + ## If desired, load the name space to allow testing of private functions
     + ## if (is.element(pkg, loadedNamespaces()))
     + ## attach(loadNamespace(pkg), name=paste("namespace", pkg, sep=":"), pos=3)
     + ##
     + ## or simply call PKG:::myPrivateFunction() in tests
     +
     + ## --- Testing ---
     +
     + ## Define tests
     + test.suite <- defineTestSuite(name=paste(pkg, "unit testing"),
     + # dirs="./RUnit",
     + dirs=path,
     + testFileRegexp = "^RUnit_tests_+",
     + testFuncRegexp = "^test.+",
     + rngKind = "Marsaglia-Multicarry",
     + rngNormalKind = "Kinderman-Ramage")
     + ## Run
     + tests <- runTestSuite(test.suite)
     +
     + ## Default report name
     + pathReport <- file.path(path, "report")
     +
     + ## Report to stdout and text files
     + cat("------------------- UNIT TEST SUMMARY ---------------------\n\n")
     + printTextProtocol(tests, showDetails=FALSE)
     + printTextProtocol(tests, showDetails=FALSE,
     + fileName=paste0(pathReport, "Summary.txt"))
     + printTextProtocol(tests, showDetails=TRUE,
     + fileName=paste0(pathReport, ".txt"))
     + ## Report to HTML file
     + printHTMLProtocol(tests, fileName=paste0(pathReport, ".html"))
     +
     + ## Return stop() to cause R CMD check stop in case of
     + ## - failures i.e. FALSE to unit tests or
     + ## - errors i.e. R errors
     + tmp <- getErrors(tests)
     + if(tmp$nFail > 0 | tmp$nErr > 0) {
     + stop(paste("\n\nunit testing failed (#test failures: ", tmp$nFail,
     + ", #R errors: ", tmp$nErr, ")\n\n", sep=""))
     + }
     + } else {
     + warning("cannot run unit tests -- package RUnit is not available")
     + }
    
     Running unit tests
     $pkg
     [1] "stremr"
    
     $getwd
     [1] "/home/hornik/tmp/R.check/r-devel-gcc/Work/PKGS/stremr.Rcheck/tests"
    
     $pathToUnitTests
     [1] "/home/hornik/tmp/R.check/r-devel-gcc/Work/PKGS/stremr.Rcheck/tests/RUnit"
    
    
    
     Executing test function test.GenericModelPredict ... Loading required package: data.table
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.6829138 1.4512950 -0.4353432 0.5852046
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "catA"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: catA"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA, catA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "CategorModel outcome: catA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA_B.1, catA_B.2, catA_B.3"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "CategorModel outcome: catA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA_B.1, catA_B.2, catA_B.3"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for outcome based on stratified model for outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: catA"
     [1] "freq counts by bin for categorical outcome: "
    
     1 2 3
     4661 4634 4694
     [1] "binned dataset: "
     sA catA_B.1 catA_B.2 catA_B.3
     [1,] 1 NA 1 NA
     [2,] 2 NA 1 NA
     [3,] 2 NA 1 NA
     [4,] 1 NA 1 NA
     [5,] 3 NA 1 NA
     [1] "fitting the model: P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     [1] "fitting the model: P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -9.762950e-08 2.155173e-06 NA
     [1] "fitting the model: P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for catA var succeeded...
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: catA"
     [1] "freq counts by bin for categorical outcome: "
    
     1 2 3
     4661 4634 4694
     [1] "binned dataset: "
     sA catA_B.1 catA_B.2 catA_B.3
     [1,] 1 NA 1 NA
     [2,] 2 NA 1 NA
     [3,] 2 NA 1 NA
     [4,] 1 NA 1 NA
     [5,] 3 NA 1 NA
     [1] "fitting the model: P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     [1] "fitting the model: P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -3.738646e-08 -2.346217e-07 -2.013073e-07
     [1] "fitting the model: P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for catA var succeeded...
     fit for catA var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: catA"
     [1] "performing prediction for categorical outcome: catA"
     [1] "performing prediction for categorical outcome: catA"
     [1] "performing prediction for outcome based on stratified model: catA"
     [1] "performing prediction for categorical outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing prediction for categorical outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     done successfully.
    
    
    
     Executing test function test.Nsamp.n.test ... done successfully.
    
    
    
     Executing test function test.options ... [1] "Possible `stremr` options:"
     [1] "fit.package" "fit.algorithm" "bin.method"
     [4] "nbins" "maxncats" "maxNperBin"
     [7] "lower_bound_zero_Q" "skip_update_zero_Q"
     Error in stremrOptions("blahblah") :
     blahblah: this options does not exist
     Error in stremrOptions("blahblah", 5) : Invalid option name: blahblah
     Error in if (!(fit.algorithm %in% allowed.fit.algorithm)) stop("fit.algorithm must be one of: " %+% :
     argument is of length zero
     Error in set_all_stremr_options(fit.package = "speedglm", fit.algorithm = "blahblah", :
     fit.algorithm must be one of: glm, gbm, randomForest, deeplearning
     Error in set_all_stremr_options(fit.package = "blahblah", fit.algorithm = "glm", :
     fit.package must be one of: speedglm, glm, h2o
     Error in set_all_stremr_options(fit.package = "speedglm", fit.algorithm = "glm", :
     bin.method must be one of: equal.mass, equal.len, dhist
     $fit.package
     [1] "speedglm"
    
     $fit.algorithm
     [1] "glm"
    
     $bin.method
     [1] "equal.mass"
    
     $nbins
     [1] 10
    
     $maxncats
     [1] 20
    
     $maxNperBin
     [1] 500
    
     $lower_bound_zero_Q
     [1] TRUE
    
     $skip_update_zero_Q
     [1] TRUE
    
     done successfully.
    
    
    
     Executing test function test.regressionCases ... done successfully.
    
    
    
     Executing test function test.t.error ... done successfully.
    
    
    
     Executing test function test.DataStorageClass ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     Error in OData$get.outvar(var = "blah") :
     requested variable blah does not exist in DataStorageClass!
     done successfully.
    
    
    
     Executing test function test.error.fits.stratify ... Error in create_subset_expr(outvars = res$outvars, stratify.EXPRS = stratify.EXPRS) :
     Could not locate the appropriate regression variable(s) within the supplied stratification list stratify_CENS, stratify_TRT or stratify_MONITOR.
     The regression outcome variable(s) specified in gform_CENS, gform_TRT or gform_MONITOR were: ( 'C,TI' )
     However, the item names in the matching stratification list were: ( 'wrongC,TI,N' )
     done successfully.
    
    
    
     Executing test function test.helperfuns ... done successfully.
    
    
    
     Executing test function test.model.fits.stratify ... done successfully.
    
    
    
     Executing test function test.model.fits.categorCENSOR ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.52652066 0.05456581 0.10858685
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.19067146 NA 0.43343872 -0.01789425
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01340964 NA NA -0.03245807 -0.01185101
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 8.599825e-13 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.29183433 -0.07998923 0.03081559
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.64534186 NA 0.09366241 -0.16923766
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01135495 NA NA -0.02269938 -0.01321850
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 1,t > 0 & C == 1)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 1"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 1"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 1 & TI == 1,t > 0 & C == 1 & TI == 1)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 1 & TI == 1"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 1 & TI == 1"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 8.599825e-13 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.29183433 -0.07998923 0.03081559
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     NA NA NA NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     NA 0.4924641 0.1270091 -0.1911502
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 1 & TI == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     NA NA NA NA NA
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 1 & TI == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     NA NA NA NA NA
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,t > 0L & TI.tminus1 == 0L,t > 0L & TI.tminus1 == 1L)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 1L"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.52652066 0.05456581 0.10858685
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.64534186 NA 0.09366241 -0.16923766
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     -0.01467019 -0.45533330 NA NA NA
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     -0.01135495 -0.02269938 -0.01321850 NA NA
     fit for N var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -21.2548627 0.9100488 2.1714524 19.1407169
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 1L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 1.092843e-07 1.158713e-07 1.320318e-07
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "performing prediction for outcome based on stratified model: TI"
     done successfully.
    
    
    
     Executing test function test.model.fits.categorCENSOR2 ... Loading required package: magrittr
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "CatC"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: CatC"
     [1] "StratifiedModel expressions: (t < 16,t == 16)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC, CatC"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     ...fitting a model for categorical censoring...
     [1] "CategorModel outcome: CatC"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC_B.1, CatC_B.2, CatC_B.3"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.1|highA1c);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.2|highA1c);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.3|highA1c);\\ Stratify: t < 16"
     ...fitting a model for categorical censoring...
     [1] "CategorModel outcome: CatC"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC_B.1, CatC_B.2, CatC_B.3"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.1|highA1c);\\ Stratify: t == 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.2|highA1c);\\ Stratify: t == 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.3|highA1c);\\ Stratify: t == 16"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,(t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L),(t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L),(t > 0L) & (barTIm1eq0 == 1L))"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI, TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L)"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L)"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (barTIm1eq0 == 1L)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: CatC"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: CatC"
     [1] "freq counts by bin for categorical outcome: "
    
     0 1 2
     7469 347 314
     [1] "binned dataset: "
     sA CatC_B.1 CatC_B.2 CatC_B.3
     [1,] 0 0 0 NA
     [2,] 0 0 0 NA
     [3,] 1 1 NA NA
     [4,] 0 0 0 NA
     [5,] 0 0 0 NA
     [1] "fitting the model: P(CatC_B.1|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -3.1487960 0.1616531
     [1] "fitting the model: P(CatC_B.2|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -3.13719779 -0.08098814
     [1] "fitting the model: P(CatC_B.3|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     NA NA
     fit for CatC var succeeded...
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: CatC"
     [1] "freq counts by bin for categorical outcome: "
    
     0 1 2
     7469 347 314
     [1] "binned dataset: "
     sA CatC_B.1 CatC_B.2 CatC_B.3
     [1,] 0 0 0 NA
     [2,] 0 0 0 NA
     [3,] 1 1 NA NA
     [4,] 0 0 0 NA
     [5,] 0 0 0 NA
     [1] "fitting the model: P(CatC_B.1|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -2.9593646 0.5614693
     [1] "fitting the model: P(CatC_B.2|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -4.89784 -15.66823
     [1] "fitting the model: P(CatC_B.3|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     NA NA
     fit for CatC var succeeded...
     fit for CatC var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.1141458 0.9100488 2.1714524 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.656607e+01 2.444839e-12 2.082888e-12 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -21.2548627 0.9100488 2.1714524 19.1407169
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: CatC"
     [1] "performing prediction for categorical outcome: CatC"
     [1] "performing prediction for categorical outcome: CatC"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "N"
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     done successfully.
    
    
    
     Executing test function test.buildingblocks ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     Error in getIPWeights(OData = OData, intervened_TRT = "TI.set1", rule_name = "TI1") :
     ...cannot locate propensity scores in 'OData' object - must run fitPropensity(...) prior to calling this function
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t < 16,t == 16)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 16"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t < 16"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.198768e-13 -5.125570e-14
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 16"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -6.143963e-14 -2.839781e-14
     fit for C var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "performing estimation for the following TRT/MONITOR rules found in column 'rule.name': TI0,TI1"
     [1] "periods"
     [1] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
     [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     [1] "Periods.0to0_TI0"
     [1] "Periods.1to1_TI0"
     [1] "Periods.2to2_TI0"
     [1] "Periods.3to3_TI0"
     [1] "Periods.4to4_TI0"
     [1] "Periods.5to5_TI0"
     [1] "Periods.6to6_TI0"
     [1] "Periods.7to7_TI0"
     [1] "Periods.8to11_TI0"
     [1] "Periods.12to15_TI0"
     [1] "Periods.0to0_TI1"
     [1] "Periods.1to1_TI1"
     [1] "Periods.2to2_TI1"
     [1] "Periods.3to3_TI1"
     [1] "Periods.4to4_TI1"
     [1] "Periods.5to5_TI1"
     [1] "Periods.6to6_TI1"
     [1] "Periods.7to7_TI1"
     [1] "Periods.8to11_TI1"
     [1] "Periods.12to15_TI1"
     ...fitting hazard MSM with speedglm::speedglm.wfit...
     [1] "MSM fits"
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     -5.465039e+00 -4.324378e+00 -4.012934e+00 -1.166619e+15
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     -6.871355e+14 -4.884654e+14 -6.732368e+00 -6.414551e+00
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     -2.490327e+15 -3.057464e+15 -3.089228e+00 -4.070768e+00
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     -4.097356e+00 -1.444049e+01 -3.626218e+00 -4.172158e+00
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     -5.928687e+00 -3.921940e+00 -4.645602e+00 -3.410729e+00
     ...evaluating MSM-based survival curves...
     ...evaluating SEs based on MSM hazard fit and the estimated IC...
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     9.379699e-17 2.900859e-16 7.383396e-15 7.293270e+00
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     6.561300e+01 4.445403e+02 3.220105e-14 2.800474e-14
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.030033e+02 7.899748e+02 7.913397e-18 2.865011e-18
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     7.009244e-18 4.879654e-08 1.399031e-19 7.292022e-18
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     2.532557e-18 1.471364e-17 3.615109e-16 1.717254e-15
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     9.340525e-15 3.126553e-15 1.800440e-14 3.336980e+14
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     7.563694e+14 1.183848e+15 5.560005e-15 5.426432e-15
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     1.830248e+14 5.408850e+14 4.968619e-15 3.569094e-15
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     6.622362e-15 1.000001e+00 8.253617e-17 2.682887e-15
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     3.708932e-15 2.085976e-15 9.255499e-15 3.032843e-15
     [1] "Should all be very small: "
     [1] 3.953818e-17 7.916801e-17 2.288376e-16 2.288376e-16 2.288376e-16
     [6] 2.288376e-16 2.227361e-16 2.339417e-16 2.339417e-16 2.339417e-16
     [11] 2.339417e-16 2.339417e-16 2.339417e-16 2.339417e-16 2.339417e-16
     [16] 2.339417e-16
     [1] "Should all be very small: "
     [1] 2.087237e-16 2.567391e-16 1.552191e-16 4.951408e-07 4.823035e-07
     [6] 4.749798e-07 4.737188e-07 4.645200e-07 4.601013e-07 4.557247e-07
     [11] 4.513896e-07 4.470959e-07 4.328058e-07 4.189726e-07 4.055814e-07
     [16] 3.926183e-07
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -2.240428e-13 -9.163027e-14
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "performing estimation for the following TRT/MONITOR rules found in column 'rule.name': TI0,TI1"
     [1] "periods"
     [1] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
     [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     [1] "Periods.0to0_TI0"
     [1] "Periods.1to1_TI0"
     [1] "Periods.2to2_TI0"
     [1] "Periods.3to3_TI0"
     [1] "Periods.4to4_TI0"
     [1] "Periods.5to5_TI0"
     [1] "Periods.6to6_TI0"
     [1] "Periods.7to7_TI0"
     [1] "Periods.8to11_TI0"
     [1] "Periods.12to15_TI0"
     [1] "Periods.0to0_TI1"
     [1] "Periods.1to1_TI1"
     [1] "Periods.2to2_TI1"
     [1] "Periods.3to3_TI1"
     [1] "Periods.4to4_TI1"
     [1] "Periods.5to5_TI1"
     [1] "Periods.6to6_TI1"
     [1] "Periods.7to7_TI1"
     [1] "Periods.8to11_TI1"
     [1] "Periods.12to15_TI1"
     ...fitting hazard MSM with speedglm::speedglm.wfit...
     [1] "MSM fits"
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     -5.479625e+00 -4.224521e+15 -4.040682e+15 -3.195295e+15
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     -3.082898e+15 -2.778817e+15 -3.052026e+15 -3.796228e+15
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     -2.715406e+15 -1.534193e+15 -3.048470e+00 -4.020852e+00
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     -4.106498e+00 -1.007712e+01 -3.450746e+00 -4.160778e+00
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     -5.909203e+00 -4.008647e+00 -4.781623e+00 -3.422484e+15
     ...evaluating MSM-based survival curves...
     ...evaluating SEs based on MSM hazard fit and the estimated IC...
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     1.363995e-15 3.892340e+00 1.153066e+02 3.014492e+03
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     2.096739e+04 2.100000e+04 1.300000e+04 5.000000e+03
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.700000e+04 1.000000e+04 2.218218e-17 1.992734e-17
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     1.087903e-17 1.670762e-05 2.380815e-17 8.984546e-17
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     4.050727e-18 8.676045e-17 3.446043e-04 2.159757e+02
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     2.012238e-14 5.581563e+13 7.715289e+13 2.180508e+14
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     2.367837e+14 2.874638e+14 2.419289e+14 1.178953e+14
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.980323e+14 4.949011e+14 9.314984e-15 1.161900e-14
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     3.404072e-15 1.000042e+00 9.042079e-16 3.580885e-15
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     4.712621e-16 6.766642e-16 1.571325e-04 1.801860e+14
     [1] "Should all be very small: "
     [1] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [6] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [11] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [16] 8.330934e-17
     [1] "Should all be very small: "
     [1] 3.999902e-16 2.024836e-16 2.525296e-16 3.877971e-05 3.758736e-05
     [6] 3.701017e-05 3.690999e-05 3.625173e-05 3.706763e-05 3.786745e-05
     [11] 3.865142e-05 3.941974e-05 3.941974e-05 3.941974e-05 3.941974e-05
     [16] 3.941974e-05
     Error in process_opt_wts(wts_data_used, weights, nodes) :
     input 'weights' must be a data.table with 3 columns, two of which must be named as: 'ID' and 't'.
     In addition: Warning messages:
     1: glm.fit: algorithm did not converge
     2: glm.fit: algorithm did not converge
     3: glm.fit: algorithm did not converge
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -5.8682574 0.2154351 3.3021509 0.4033691 NA 0.7501467 NA
     [1] "Surv est: 0.983758322675102"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=0: 0.01624"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -4.67474313 0.19724908 2.21184261 -0.09839186 0.76483183 0.36869687
     TI.tminus1
     -0.98759997
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.48082464 0.25283340 2.46508499 0.04786835 NA -0.43706261
     TI.tminus1
     NA
     [1] "Surv est: 0.969902221464484"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=1: 0.0301"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.8073588 -1.1071567 1.3574257 -0.4540453 0.6083749 0.3767599 -1.4726757
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7570081 -0.3346276 1.4801253 -0.3532999 0.5055449 -0.5127511 -0.6589153
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.90325161 -0.07708853 2.01607750 -0.02829320 NA -0.32644563
     TI.tminus1
     NA
     [1] "Surv est: 0.953782240282527"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=2: 0.04622"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.2729961 0.6045142 2.3185601 -1.4506484 0.4525435 -1.0902410 -1.7027505
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.45925760 -0.49121038 1.40054082 -0.35287095 0.50934192 -0.02283871
     TI.tminus1
     -1.28687470
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8442520 -0.1010111 1.5056775 -0.2372471 0.4546915 -0.4782690 -0.6244729
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.94053966 0.04857403 1.99765895 0.01058704 NA -0.32554792
     TI.tminus1
     NA
     [1] "Surv est: 0.953681572539541"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04632"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.0863662 1.4415952 1.1242617 -0.4941329 -0.1391926 -0.8298997 -0.6156850
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1883548 1.2010569 1.3144619 -0.3947993 0.1333006 -0.9913184 -0.5170650
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.11978976 0.36019767 1.14780785 -0.23837798 0.37263297 -0.05869163
     TI.tminus1
     -0.85675524
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.6602088 0.3624027 1.3288288 -0.1996436 0.3619692 -0.4185487 -0.4804042
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.757594710 0.346812991 1.758549008 0.002438552 NA -0.302239540
     TI.tminus1
     NA
     [1] "Surv est: 0.943575229684677"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.05642"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.694637 0.368584 3.290803 -0.666631 NA NA NA
     [1] "tmle update: -0.00149135496809919"
     [1] "Surv est: 0.984107401301778"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=0: 0.01589"
     [1] "...empirical mean of the estimated EIC: -3.09079900454493e-05"
     [1] "...estimated TMLE variance: 2.41999050417123e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8004930 0.9282348 0.6879804 -0.5514791 0.7438655 NA NA
     [1] "tmle update: 0.0727160966327068"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6000572 0.5722892 2.2618565 -0.7563574 NA NA NA
     [1] "tmle update: -0.0022357049164653"
     [1] "Surv est: 0.969834495012909"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=1: 0.03017"
     [1] "...empirical mean of the estimated EIC: -6.07101133764977e-05"
     [1] "...estimated TMLE variance: 6.61356670225727e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9817186 -17.2807447 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595614761723"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715771607933"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470300657529"
     [1] "Surv est: 0.951909613102674"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=2: 0.04809"
     [1] "...empirical mean of the estimated EIC: -0.00010436571628225"
     [1] "...estimated TMLE variance: 0.000251078927354862"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595625433471"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715771369513"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470300648418"
     [1] "Surv est: 0.95190961310293"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04809"
     [1] "...empirical mean of the estimated EIC: -0.000104365720571848"
     [1] "...estimated TMLE variance: 0.000251078927359577"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.209019147885717"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8958776 0.4984205 0.7750137 1.4400473 0.1142727 NA NA
     [1] "tmle update: 0.0520880449204392"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1879874 -0.3427790 0.1064457 -0.4879009 0.5164562 NA NA
     [1] "tmle update: -0.00448980897354264"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7827815 0.1202478 0.3514419 -0.6841186 0.4586810 NA NA
     [1] "tmle update: 0.0158905661689546"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.4482301 0.1976754 1.4967452 -0.5174974 NA NA NA
     [1] "tmle update: -0.00227377143477276"
     [1] "Surv est: 0.925542187707399"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.07446"
     [1] "...empirical mean of the estimated EIC: -0.000520790968265705"
     [1] "...estimated TMLE variance: 0.00803708770988044"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.0048959544125669"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715758304584"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470301977723"
     [1] "Surv est: 0.951909613112289"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04809"
     [1] "...empirical mean of the estimated EIC: -1.65538533979754e-05"
     [1] "...estimated TMLE variance: 8.3806787779791e-06"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.209019147869959"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8958776 0.4984205 0.7750137 1.4400473 0.1142727 NA NA
     [1] "tmle update: 0.0520880449202836"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1879874 -0.3427790 0.1064457 -0.4879009 0.5164562 NA NA
     [1] "tmle update: -0.00448980955099783"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7827815 0.1202478 0.3514419 -0.6841186 0.4586810 NA NA
     [1] "tmle update: 0.0158905661764066"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.4482301 0.1976754 1.4967452 -0.5174974 NA NA NA
     [1] "tmle update: -0.00227377139578826"
     [1] "Surv est: 0.925542187729508"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.07446"
     [1] "...empirical mean of the estimated EIC: -8.12433860103523e-05"
     [1] "...estimated TMLE variance: 0.00019629047768188"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: 0.00455038396959821"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5351943 -0.2698513 0.0819634 -1.1897532 1.1194722 NA NA
     [1] "tmle update: 0.00148791277372786"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.9037005 0.1316045 1.9048099 -0.7888752 NA NA NA
     [1] "tmle update: 0.0038737545211174"
     [1] "Surv est: 0.952423126954576"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04758"
     [1] "...empirical mean of the estimated EIC: -3.11352727229658e-05"
     [1] "...estimated TMLE variance: 4.05438882728483e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.0043556607594549"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -5.1065413 0.4996280 0.7537557 1.4595663 0.1268353 NA NA
     [1] "tmle update: -6.23198919478809e-11"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.365723662 -0.465839994 0.005840225 -0.509288785 0.596038204 NA
     TI.tminus1
     NA
     [1] "tmle update: -4.44506521637441e-10"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.88176714 0.08310961 0.32781298 -0.75064933 0.51647978 NA
     TI.tminus1
     NA
     [1] "tmle update: 5.99566016142493e-11"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.5397115 0.1898817 1.5664979 -0.5505100 NA NA NA
     [1] "tmle update: 0.0027933549293886"
     [1] "Surv est: 0.931389922902869"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.06861"
     [1] "...empirical mean of the estimated EIC: -3.04000131367507e-05"
     [1] "...estimated TMLE variance: 5.41527268962014e-05"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -2.240428e-13 -9.163027e-14
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -4.661343e-14 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.830025e-13 -7.964050e-14
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     1.2490429 NA -0.4673254 -0.1775312
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.03015004 NA NA 0.01124218 -0.01120127
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -4.661343e-14 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.830025e-13 -7.964050e-14
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     1.2490429 NA -0.4673254 -0.1775312
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.03015004 NA NA 0.01124218 -0.01120127
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     done successfully.
    
    
    
     Executing test function test.speedglm.allestimators10Kdata ... [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     writing report to directory: /home/hornik/tmp/scratch/RtmpQnYjqs
     writing related figures to report subdirectory: figure.sim.data.example.fup2
    
    
     processing file: /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-3 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-4 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     label: unnamed-chunk-5 (with options)
     List of 1
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
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     inline R code fragments
    
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     List of 1
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     label: unnamed-chunk-9 (with options)
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     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
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     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
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     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
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     List of 2
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     $ results: chr "asis"
    
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     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
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     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
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     $ results: chr "asis"
    
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     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
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     List of 2
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     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /home/hornik/tmp/scratch/RtmpQnYjqs/sim.data.example.fup2.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-devel-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /home/hornik/tmp/scratch/RtmpQnYjqs/rmarkdown-str1fb370257e34.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup2.html
     writing report to directory: /home/hornik/tmp/scratch/RtmpQnYjqs
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
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     $ results: chr "asis"
    
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     label: unnamed-chunk-3 (with options)
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     $ results: chr "asis"
    
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     label: unnamed-chunk-4 (with options)
     List of 2
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     $ results: chr "asis"
    
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     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
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     inline R code fragments
    
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     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
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     $ results: chr "asis"
    
     inline R code fragments
    
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     List of 4
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     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
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     List of 1
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     label: unnamed-chunk-14 (with options)
     List of 4
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     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
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     List of 2
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     $ results: chr "asis"
    
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     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
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     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /home/hornik/tmp/scratch/RtmpQnYjqs/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-devel-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /home/hornik/tmp/scratch/RtmpQnYjqs/rmarkdown-str1fb32ce76a75.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /home/hornik/tmp/scratch/RtmpQnYjqs
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-3 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-4 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     label: unnamed-chunk-5 (with options)
     List of 1
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-7 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-8 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-9 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /home/hornik/tmp/scratch/RtmpQnYjqs/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-devel-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /home/hornik/tmp/scratch/RtmpQnYjqs/rmarkdown-str1fb347ea7b43.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /home/hornik/tmp/scratch/RtmpQnYjqs
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-3 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-4 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     label: unnamed-chunk-5 (with options)
     List of 1
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-7 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-8 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-9 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /home/hornik/tmp/scratch/RtmpQnYjqs/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-devel-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /home/hornik/tmp/scratch/RtmpQnYjqs/rmarkdown-str1fb3651d124c.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /home/hornik/tmp/scratch/RtmpQnYjqs
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-3 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-4 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     label: unnamed-chunk-5 (with options)
     List of 1
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-7 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-8 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-9 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /home/hornik/tmp/scratch/RtmpQnYjqs/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-devel-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /home/hornik/tmp/scratch/RtmpQnYjqs/rmarkdown-str1fb34ef4196f.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /home/hornik/tmp/scratch/RtmpQnYjqs
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-3 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-4 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     label: unnamed-chunk-5 (with options)
     List of 1
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-7 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-8 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-9 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /home/hornik/tmp/scratch/RtmpQnYjqs/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-devel-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /home/hornik/tmp/scratch/RtmpQnYjqs/rmarkdown-str1fb34e99c1f1.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /home/hornik/tmp/scratch/RtmpQnYjqs
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-3 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-4 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     label: unnamed-chunk-5 (with options)
     List of 1
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-7 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-8 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-9 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /home/hornik/tmp/scratch/RtmpQnYjqs/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-devel-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /home/hornik/tmp/scratch/RtmpQnYjqs/rmarkdown-str1fb3202848fb.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
    
    
     processing file: /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
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     $ fig.width : num 5
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     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     !!! Error: Cannot write tmp file `tmp-pdfcrop-10839.tex' (Read-only file system)!
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     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     !!! Error: Cannot write tmp file `tmp-pdfcrop-11170.tex' (Read-only file system)!
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     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
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     output file: /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /home/hornik/tmp/scratch/RtmpQnYjqs/report-script-rmd.utf8.md --to latex --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /home/hornik/tmp/scratch/RtmpQnYjqs/sim.data.example.fup.tex --table-of-contents --toc-depth 2 --template /home/hornik/tmp/R.check/r-devel-gcc/Work/build/Packages/rmarkdown/rmd/latex/default-1.17.0.2.tex --number-sections --highlight-style tango --latex-engine pdflatex --variable graphics=yes --variable 'geometry:margin=1in'
     You are recommended to install the tinytex package to build PDF.FALSE
     Latexmk: This is Latexmk, John Collins, 1 January 2015, version: 4.41.
     Cannot write file 'sim.data.example.fup.aux'
    
     Latexmk, John Collins, 1 January 2015. Version 4.41
     Timing stopped at: 29.73 1.471 48.85
     Error in make_report_rmd(OData, NPMSM = list(surv1, surv2), MSM = MSM.IPAW, :
     Failed to compile /home/hornik/tmp/scratch/RtmpQnYjqs/sim.data.example.fup.tex.
     done successfully.
    
    
    
     Executing test function test.speedglm.stochastic.TMLE.NDE.1Kdata ... done successfully.
    
    
    
     Executing test function test.GCOMP.TMLE.10Kdata ... done successfully.
    
    
    
     Executing test function test.directRegressionDefn.10Kdata ... done successfully.
    
    
    
     Executing test function test.iterTMLE.10Kdata ... done successfully.
    
    
    
     Executing test function test.ContinModel ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "continA"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: continA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "ContinModel outcome: continA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: continA_B.1, continA_B.2, continA_B.3, continA_B.4, continA_B.5, continA_B.6, continA_B.7, continA_B.8, continA_B.9, continA_B.10, continA_B.11, continA_B.12, continA_B.13, continA_B.14, continA_B.15, continA_B.16, continA_B.17, continA_B.18, continA_B.19, continA_B.20, continA_B.21, continA_B.22, continA_B.23, continA_B.24, continA_B.25, continA_B.26, continA_B.27, continA_B.28, continA_B.29"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 29"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.4|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.5|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.6|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.7|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.8|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.9|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.10|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.11|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.12|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.13|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.14|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.15|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.16|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.17|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.18|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.19|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.20|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.21|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.22|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.23|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.24|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.25|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.26|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.27|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.28|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.29|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for continuous outcome: continA"
     [1] "freq counts by bin for continuous outcome: "
    
     2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
     519 518 518 518 518 518 518 518 518 518 518 518 518 519 518 518 518 518 518 518 518 518 518 518 518
     27 28
     518 519
     [1] "binned dataset: "
     continA_B.1 continA_B.2 continA_B.3 continA_B.4 continA_B.5 continA_B.6 continA_B.7
     [1,] 14 0 0 0 0 0 0 0
     [2,] 10 0 0 0 0 0 0 0
     [3,] 25 0 0 0 0 0 0 0
     [4,] 17 0 0 0 0 0 0 0
     [5,] 24 0 0 0 0 0 0 0
     continA_B.8 continA_B.9 continA_B.10 continA_B.11 continA_B.12 continA_B.13 continA_B.14
     [1,] 0 0 0 0 0 0 1
     [2,] 0 0 1 NA NA NA NA
     [3,] 0 0 0 0 0 0 0
     [4,] 0 0 0 0 0 0 0
     [5,] 0 0 0 0 0 0 0
     continA_B.15 continA_B.16 continA_B.17 continA_B.18 continA_B.19 continA_B.20 continA_B.21
     [1,] NA NA NA NA NA NA NA
     [2,] NA NA NA NA NA NA NA
     [3,] 0 0 0 0 0 0 0
     [4,] 0 0 1 NA NA NA NA
     [5,] 0 0 0 0 0 0 0
     continA_B.22 continA_B.23 continA_B.24 continA_B.25 continA_B.26 continA_B.27 continA_B.28
     [1,] NA NA NA NA NA NA NA
     [2,] NA NA NA NA NA NA NA
     [3,] 0 0 0 1 NA NA NA
     [4,] NA NA NA NA NA NA NA
     [5,] 0 0 1 NA NA NA NA
     continA_B.29
     [1,] NA
     [2,] NA
     [3,] NA
     [4,] NA
     [5,] NA
     [1] "fitting the model: P(continA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.656607e+01 -1.172459e-11 -1.310221e-11 -2.568646e-11
     [1] "fitting the model: P(continA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.28414572 0.03174946 0.07155323 0.01813534
     [1] "fitting the model: P(continA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.21395602 -0.06457574 -0.13312194 0.05019774
     [1] "fitting the model: P(continA_B.4|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.1297687244 -0.0007524009 -0.1062959488 -0.0532131704
     [1] "fitting the model: P(continA_B.5|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.13833535 0.27160986 0.02047098 -0.06584771
     [1] "fitting the model: P(continA_B.6|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.993767433 -0.020499725 0.007943424 -0.189135149
     [1] "fitting the model: P(continA_B.7|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.02971523 -0.07942120 -0.17114837 0.04731996
     [1] "fitting the model: P(continA_B.8|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.96582449 0.01442130 -0.02593898 -0.05007518
     [1] "fitting the model: P(continA_B.9|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.96127340 0.27814254 -0.05268694 -0.01273720
     [1] "fitting the model: P(continA_B.10|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.875519103 -0.055275528 -0.035222549 -0.004201964
     [1] "fitting the model: P(continA_B.11|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.83159769 0.09789627 -0.17833380 0.03882315
     [1] "fitting the model: P(continA_B.12|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.781662359 -0.022929565 0.042464981 0.004605334
     [1] "fitting the model: P(continA_B.13|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.70500758 0.23176541 -0.01622940 -0.05123314
     [1] "fitting the model: P(continA_B.14|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.70158580 0.29801235 -0.13953416 0.09864492
     [1] "fitting the model: P(continA_B.15|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.6132938 -0.3012726 0.1285447 0.0917634
     [1] "fitting the model: P(continA_B.16|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.3704240 -0.1118700 -0.1106714 -0.1582323
     [1] "fitting the model: P(continA_B.17|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.343142257 -0.110859172 -0.002515909 -0.081831586
     [1] "fitting the model: P(continA_B.18|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.28440780 -0.04763716 0.03722076 -0.03953874
     [1] "fitting the model: P(continA_B.19|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.198639223 -0.269818397 0.119043968 0.003616638
     [1] "fitting the model: P(continA_B.20|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.16235126 0.19791866 0.23275592 0.01724836
     [1] "fitting the model: P(continA_B.21|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.95959533 -0.12963827 0.05533215 0.02878056
     [1] "fitting the model: P(continA_B.22|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.79934783 0.07045687 -0.14301407 0.04873087
     [1] "fitting the model: P(continA_B.23|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.61825522 0.03469318 0.08166859 -0.02248664
     [1] "fitting the model: P(continA_B.24|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.47302660 0.23117727 0.01920899 0.10327734
     [1] "fitting the model: P(continA_B.25|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.11097501 0.05437560 0.06473488 -0.01292941
     [1] "fitting the model: P(continA_B.26|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -0.692367203 -0.048547039 0.035410760 -0.007121965
     [1] "fitting the model: P(continA_B.27|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.008204018 -0.450138223 -0.124861390 0.112455844
     [1] "fitting the model: P(continA_B.28|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 5.977860e-09 5.386376e-09 4.718384e-06
     [1] "fitting the model: P(continA_B.29|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for outcome continA succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for continuous outcome: continA"
     [1] "performing prediction for continuous outcome: continA"
     done successfully.
    
     ------------------- UNIT TEST SUMMARY ---------------------
    
     RUNIT TEST PROTOCOL -- Mon Apr 16 08:42:02 2018
     ***********************************************
     Number of test functions: 18
     Number of errors: 1
     Number of failures: 0
    
    
     1 Test Suite :
     stremr unit testing - 18 test functions, 1 error, 0 failures
     ERROR in test.speedglm.allestimators10Kdata: Error in make_report_rmd(OData, NPMSM = list(surv1, surv2), MSM = MSM.IPAW, :
     Failed to compile /home/hornik/tmp/scratch/RtmpQnYjqs/sim.data.example.fup.tex.
     Error:
    
     unit testing failed (#test failures: 0, #R errors: 1)
    
     Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.4
Check: tests
Result: ERROR
     Running ‘test-all.R’ [164s/189s]
    Running the tests in ‘tests/test-all.R’ failed.
    Complete output:
     > ## unit tests will not be done if RUnit is not available
     > # setwd("..")
     > # getwd()
     > # library(RUnit)
     > if(require("RUnit", quietly=TRUE)) {
     + ## --- Setup ---
     +
     + pkg <- "stremr" # <-- Tested package name
     +
     + if(Sys.getenv("RCMDCHECK") == "FALSE") {
     + ## Path to unit tests for standalone running under Makefile (not R CMD check)
     + ## PKG/tests/../inst/unitTests
     + # path <- file.path(getwd(), "..", "inst", "unitTests")
     + } else {
     + ## Path to unit tests for R CMD check
     + ## PKG.Rcheck/tests/../PKG/unitTests
     + # path <- system.file(package=pkg, "RUnit")
     +
     + # REPLACED WITH:
     + path <- file.path(getwd(), "RUnit")
     + }
     +
     + cat("\nRunning unit tests\n")
     + print(list(pkg=pkg, getwd=getwd(), pathToUnitTests=path))
     +
     + library(package=pkg, character.only=TRUE)
     +
     + ## If desired, load the name space to allow testing of private functions
     + ## if (is.element(pkg, loadedNamespaces()))
     + ## attach(loadNamespace(pkg), name=paste("namespace", pkg, sep=":"), pos=3)
     + ##
     + ## or simply call PKG:::myPrivateFunction() in tests
     +
     + ## --- Testing ---
     +
     + ## Define tests
     + test.suite <- defineTestSuite(name=paste(pkg, "unit testing"),
     + # dirs="./RUnit",
     + dirs=path,
     + testFileRegexp = "^RUnit_tests_+",
     + testFuncRegexp = "^test.+",
     + rngKind = "Marsaglia-Multicarry",
     + rngNormalKind = "Kinderman-Ramage")
     + ## Run
     + tests <- runTestSuite(test.suite)
     +
     + ## Default report name
     + pathReport <- file.path(path, "report")
     +
     + ## Report to stdout and text files
     + cat("------------------- UNIT TEST SUMMARY ---------------------\n\n")
     + printTextProtocol(tests, showDetails=FALSE)
     + printTextProtocol(tests, showDetails=FALSE,
     + fileName=paste0(pathReport, "Summary.txt"))
     + printTextProtocol(tests, showDetails=TRUE,
     + fileName=paste0(pathReport, ".txt"))
     + ## Report to HTML file
     + printHTMLProtocol(tests, fileName=paste0(pathReport, ".html"))
     +
     + ## Return stop() to cause R CMD check stop in case of
     + ## - failures i.e. FALSE to unit tests or
     + ## - errors i.e. R errors
     + tmp <- getErrors(tests)
     + if(tmp$nFail > 0 | tmp$nErr > 0) {
     + stop(paste("\n\nunit testing failed (#test failures: ", tmp$nFail,
     + ", #R errors: ", tmp$nErr, ")\n\n", sep=""))
     + }
     + } else {
     + warning("cannot run unit tests -- package RUnit is not available")
     + }
    
     Running unit tests
     $pkg
     [1] "stremr"
    
     $getwd
     [1] "/data/gannet/ripley/R/packages/tests-clang/stremr.Rcheck/tests"
    
     $pathToUnitTests
     [1] "/data/gannet/ripley/R/packages/tests-clang/stremr.Rcheck/tests/RUnit"
    
    
    
     Executing test function test.GenericModelPredict ... Loading required package: data.table
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.6829138 1.4512950 -0.4353432 0.5852046
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "catA"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: catA"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA, catA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "CategorModel outcome: catA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA_B.1, catA_B.2, catA_B.3"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "CategorModel outcome: catA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA_B.1, catA_B.2, catA_B.3"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for outcome based on stratified model for outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: catA"
     [1] "freq counts by bin for categorical outcome: "
    
     1 2 3
     4610 4635 4744
     [1] "binned dataset: "
     sA catA_B.1 catA_B.2 catA_B.3
     [1,] 1 NA 1 NA
     [2,] 3 NA 1 NA
     [3,] 2 NA 1 NA
     [4,] 3 NA 1 NA
     [5,] 1 NA 1 NA
     [1] "fitting the model: P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     [1] "fitting the model: P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -9.762950e-08 2.155173e-06 NA
     [1] "fitting the model: P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for catA var succeeded...
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: catA"
     [1] "freq counts by bin for categorical outcome: "
    
     1 2 3
     4610 4635 4744
     [1] "binned dataset: "
     sA catA_B.1 catA_B.2 catA_B.3
     [1,] 1 NA 1 NA
     [2,] 3 NA 1 NA
     [3,] 2 NA 1 NA
     [4,] 3 NA 1 NA
     [5,] 1 NA 1 NA
     [1] "fitting the model: P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     [1] "fitting the model: P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -3.738646e-08 -2.346217e-07 -2.013073e-07
     [1] "fitting the model: P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for catA var succeeded...
     fit for catA var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: catA"
     [1] "performing prediction for categorical outcome: catA"
     [1] "performing prediction for categorical outcome: catA"
     [1] "performing prediction for outcome based on stratified model: catA"
     [1] "performing prediction for categorical outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing prediction for categorical outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     done successfully.
    
    
    
     Executing test function test.Nsamp.n.test ... done successfully.
    
    
    
     Executing test function test.options ... [1] "Possible `stremr` options:"
     [1] "fit.package" "fit.algorithm" "bin.method"
     [4] "nbins" "maxncats" "maxNperBin"
     [7] "lower_bound_zero_Q" "skip_update_zero_Q"
     Error in stremrOptions("blahblah") :
     blahblah: this options does not exist
     Error in stremrOptions("blahblah", 5) : Invalid option name: blahblah
     Error in if (!(fit.algorithm %in% allowed.fit.algorithm)) stop("fit.algorithm must be one of: " %+% :
     argument is of length zero
     Error in set_all_stremr_options(fit.package = "speedglm", fit.algorithm = "blahblah", :
     fit.algorithm must be one of: glm, gbm, randomForest, deeplearning
     Error in set_all_stremr_options(fit.package = "blahblah", fit.algorithm = "glm", :
     fit.package must be one of: speedglm, glm, h2o
     Error in set_all_stremr_options(fit.package = "speedglm", fit.algorithm = "glm", :
     bin.method must be one of: equal.mass, equal.len, dhist
     $fit.package
     [1] "speedglm"
    
     $fit.algorithm
     [1] "glm"
    
     $bin.method
     [1] "equal.mass"
    
     $nbins
     [1] 10
    
     $maxncats
     [1] 20
    
     $maxNperBin
     [1] 500
    
     $lower_bound_zero_Q
     [1] TRUE
    
     $skip_update_zero_Q
     [1] TRUE
    
     done successfully.
    
    
    
     Executing test function test.regressionCases ... done successfully.
    
    
    
     Executing test function test.t.error ... done successfully.
    
    
    
     Executing test function test.DataStorageClass ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     Error in OData$get.outvar(var = "blah") :
     requested variable blah does not exist in DataStorageClass!
     done successfully.
    
    
    
     Executing test function test.error.fits.stratify ... Error in create_subset_expr(outvars = res$outvars, stratify.EXPRS = stratify.EXPRS) :
     Could not locate the appropriate regression variable(s) within the supplied stratification list stratify_CENS, stratify_TRT or stratify_MONITOR.
     The regression outcome variable(s) specified in gform_CENS, gform_TRT or gform_MONITOR were: ( 'C,TI' )
     However, the item names in the matching stratification list were: ( 'wrongC,TI,N' )
     done successfully.
    
    
    
     Executing test function test.helperfuns ... done successfully.
    
    
    
     Executing test function test.model.fits.stratify ... done successfully.
    
    
    
     Executing test function test.model.fits.categorCENSOR ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.52652066 0.05456581 0.10858685
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.19067146 NA 0.43343872 -0.01789425
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01340964 NA NA -0.03245807 -0.01185101
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 8.599825e-13 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.29183433 -0.07998923 0.03081559
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.64534186 NA 0.09366241 -0.16923766
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01135495 NA NA -0.02269938 -0.01321850
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 1,t > 0 & C == 1)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 1"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 1"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 1 & TI == 1,t > 0 & C == 1 & TI == 1)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 1 & TI == 1"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 1 & TI == 1"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 8.599825e-13 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.29183433 -0.07998923 0.03081559
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     NA NA NA NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     NA 0.4924641 0.1270091 -0.1911502
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 1 & TI == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     NA NA NA NA NA
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 1 & TI == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     NA NA NA NA NA
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,t > 0L & TI.tminus1 == 0L,t > 0L & TI.tminus1 == 1L)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 1L"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.52652066 0.05456581 0.10858685
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.64534186 NA 0.09366241 -0.16923766
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     -0.01467019 -0.45533330 NA NA NA
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     -0.01135495 -0.02269938 -0.01321850 NA NA
     fit for N var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -21.2548627 0.9100488 2.1714524 19.1407169
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 1L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 1.092843e-07 1.158713e-07 1.320318e-07
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "performing prediction for outcome based on stratified model: TI"
     done successfully.
    
    
    
     Executing test function test.model.fits.categorCENSOR2 ... Loading required package: magrittr
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "CatC"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: CatC"
     [1] "StratifiedModel expressions: (t < 16,t == 16)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC, CatC"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     ...fitting a model for categorical censoring...
     [1] "CategorModel outcome: CatC"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC_B.1, CatC_B.2, CatC_B.3"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.1|highA1c);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.2|highA1c);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.3|highA1c);\\ Stratify: t < 16"
     ...fitting a model for categorical censoring...
     [1] "CategorModel outcome: CatC"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC_B.1, CatC_B.2, CatC_B.3"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.1|highA1c);\\ Stratify: t == 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.2|highA1c);\\ Stratify: t == 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.3|highA1c);\\ Stratify: t == 16"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,(t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L),(t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L),(t > 0L) & (barTIm1eq0 == 1L))"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI, TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L)"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L)"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (barTIm1eq0 == 1L)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: CatC"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: CatC"
     [1] "freq counts by bin for categorical outcome: "
    
     0 1 2
     7469 347 314
     [1] "binned dataset: "
     sA CatC_B.1 CatC_B.2 CatC_B.3
     [1,] 0 0 0 NA
     [2,] 0 0 0 NA
     [3,] 1 1 NA NA
     [4,] 0 0 0 NA
     [5,] 0 0 0 NA
     [1] "fitting the model: P(CatC_B.1|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -3.1487960 0.1616531
     [1] "fitting the model: P(CatC_B.2|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -3.13719779 -0.08098814
     [1] "fitting the model: P(CatC_B.3|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     NA NA
     fit for CatC var succeeded...
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: CatC"
     [1] "freq counts by bin for categorical outcome: "
    
     0 1 2
     7469 347 314
     [1] "binned dataset: "
     sA CatC_B.1 CatC_B.2 CatC_B.3
     [1,] 0 0 0 NA
     [2,] 0 0 0 NA
     [3,] 1 1 NA NA
     [4,] 0 0 0 NA
     [5,] 0 0 0 NA
     [1] "fitting the model: P(CatC_B.1|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -2.9593646 0.5614693
     [1] "fitting the model: P(CatC_B.2|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -4.89784 -15.66823
     [1] "fitting the model: P(CatC_B.3|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     NA NA
     fit for CatC var succeeded...
     fit for CatC var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.1141458 0.9100488 2.1714524 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.656607e+01 2.444839e-12 2.082888e-12 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -21.2548627 0.9100488 2.1714524 19.1407169
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: CatC"
     [1] "performing prediction for categorical outcome: CatC"
     [1] "performing prediction for categorical outcome: CatC"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "N"
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     done successfully.
    
    
    
     Executing test function test.buildingblocks ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     Error in getIPWeights(OData = OData, intervened_TRT = "TI.set1", rule_name = "TI1") :
     ...cannot locate propensity scores in 'OData' object - must run fitPropensity(...) prior to calling this function
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t < 16,t == 16)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 16"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t < 16"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.198768e-13 -5.125570e-14
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 16"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -6.143963e-14 -2.839781e-14
     fit for C var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "performing estimation for the following TRT/MONITOR rules found in column 'rule.name': TI0,TI1"
     [1] "periods"
     [1] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
     [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     [1] "Periods.0to0_TI0"
     [1] "Periods.1to1_TI0"
     [1] "Periods.2to2_TI0"
     [1] "Periods.3to3_TI0"
     [1] "Periods.4to4_TI0"
     [1] "Periods.5to5_TI0"
     [1] "Periods.6to6_TI0"
     [1] "Periods.7to7_TI0"
     [1] "Periods.8to11_TI0"
     [1] "Periods.12to15_TI0"
     [1] "Periods.0to0_TI1"
     [1] "Periods.1to1_TI1"
     [1] "Periods.2to2_TI1"
     [1] "Periods.3to3_TI1"
     [1] "Periods.4to4_TI1"
     [1] "Periods.5to5_TI1"
     [1] "Periods.6to6_TI1"
     [1] "Periods.7to7_TI1"
     [1] "Periods.8to11_TI1"
     [1] "Periods.12to15_TI1"
     ...fitting hazard MSM with speedglm::speedglm.wfit...
     [1] "MSM fits"
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     -5.465039e+00 -4.324378e+00 -4.012934e+00 -1.166619e+15
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     -6.871355e+14 -4.884654e+14 -6.732368e+00 -6.414551e+00
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     -2.490327e+15 -3.057464e+15 -3.089228e+00 -4.070768e+00
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     -4.097356e+00 -1.444049e+01 -3.626218e+00 -4.172158e+00
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     -5.928687e+00 -3.921940e+00 -4.645602e+00 -3.410729e+00
     ...evaluating MSM-based survival curves...
     ...evaluating SEs based on MSM hazard fit and the estimated IC...
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     9.379699e-17 2.900859e-16 7.383396e-15 7.293270e+00
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     6.561300e+01 4.445403e+02 3.220105e-14 2.800474e-14
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.030033e+02 7.899748e+02 7.913397e-18 2.865011e-18
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     7.009244e-18 4.879654e-08 1.399031e-19 7.292022e-18
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     2.532557e-18 1.471364e-17 3.615109e-16 1.717254e-15
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     9.340525e-15 3.126553e-15 1.800440e-14 3.336980e+14
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     7.563694e+14 1.183848e+15 5.560005e-15 5.426432e-15
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     1.830248e+14 5.408850e+14 4.968619e-15 3.569094e-15
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     6.622362e-15 1.000001e+00 8.253617e-17 2.682887e-15
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     3.708932e-15 2.085976e-15 9.255499e-15 3.032843e-15
     [1] "Should all be very small: "
     [1] 3.953818e-17 7.916801e-17 2.288376e-16 2.288376e-16 2.288376e-16
     [6] 2.288376e-16 2.227361e-16 2.339417e-16 2.339417e-16 2.339417e-16
     [11] 2.339417e-16 2.339417e-16 2.339417e-16 2.339417e-16 2.339417e-16
     [16] 2.339417e-16
     [1] "Should all be very small: "
     [1] 2.087237e-16 2.567391e-16 1.552191e-16 4.951408e-07 4.823035e-07
     [6] 4.749798e-07 4.737188e-07 4.645200e-07 4.601013e-07 4.557247e-07
     [11] 4.513896e-07 4.470959e-07 4.328058e-07 4.189726e-07 4.055814e-07
     [16] 3.926183e-07
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -2.240428e-13 -9.163027e-14
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "performing estimation for the following TRT/MONITOR rules found in column 'rule.name': TI0,TI1"
     [1] "periods"
     [1] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
     [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     [1] "Periods.0to0_TI0"
     [1] "Periods.1to1_TI0"
     [1] "Periods.2to2_TI0"
     [1] "Periods.3to3_TI0"
     [1] "Periods.4to4_TI0"
     [1] "Periods.5to5_TI0"
     [1] "Periods.6to6_TI0"
     [1] "Periods.7to7_TI0"
     [1] "Periods.8to11_TI0"
     [1] "Periods.12to15_TI0"
     [1] "Periods.0to0_TI1"
     [1] "Periods.1to1_TI1"
     [1] "Periods.2to2_TI1"
     [1] "Periods.3to3_TI1"
     [1] "Periods.4to4_TI1"
     [1] "Periods.5to5_TI1"
     [1] "Periods.6to6_TI1"
     [1] "Periods.7to7_TI1"
     [1] "Periods.8to11_TI1"
     [1] "Periods.12to15_TI1"
     ...fitting hazard MSM with speedglm::speedglm.wfit...
     [1] "MSM fits"
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     -5.479625e+00 -4.224521e+15 -4.040682e+15 -3.195295e+15
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     -3.082898e+15 -2.778817e+15 -3.052026e+15 -3.796228e+15
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     -2.715406e+15 -1.534193e+15 -3.048470e+00 -4.020852e+00
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     -4.106498e+00 -1.007712e+01 -3.450746e+00 -4.160778e+00
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     -5.909203e+00 -4.008647e+00 -4.781623e+00 -3.422484e+15
     ...evaluating MSM-based survival curves...
     ...evaluating SEs based on MSM hazard fit and the estimated IC...
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     1.363995e-15 3.892340e+00 1.153066e+02 3.014492e+03
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     2.096739e+04 2.100000e+04 1.300000e+04 5.000000e+03
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.700000e+04 1.000000e+04 2.218218e-17 1.992734e-17
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     1.087903e-17 1.670762e-05 2.380815e-17 8.984546e-17
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     4.050727e-18 8.676045e-17 3.446043e-04 2.159757e+02
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     2.012238e-14 5.581563e+13 7.715289e+13 2.180508e+14
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     2.367837e+14 2.874638e+14 2.419289e+14 1.178953e+14
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.980323e+14 4.949011e+14 9.314984e-15 1.161900e-14
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     3.404072e-15 1.000042e+00 9.042079e-16 3.580885e-15
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     4.712621e-16 6.766642e-16 1.571325e-04 1.801860e+14
     [1] "Should all be very small: "
     [1] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [6] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [11] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [16] 8.330934e-17
     [1] "Should all be very small: "
     [1] 3.999902e-16 2.024836e-16 2.525296e-16 3.877971e-05 3.758736e-05
     [6] 3.701017e-05 3.690999e-05 3.625173e-05 3.706763e-05 3.786745e-05
     [11] 3.865142e-05 3.941974e-05 3.941974e-05 3.941974e-05 3.941974e-05
     [16] 3.941974e-05
     Error in process_opt_wts(wts_data_used, weights, nodes) :
     input 'weights' must be a data.table with 3 columns, two of which must be named as: 'ID' and 't'.
     In addition: Warning messages:
     1: glm.fit: algorithm did not converge
     2: glm.fit: algorithm did not converge
     3: glm.fit: algorithm did not converge
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -5.8682574 0.2154351 3.3021509 0.4033691 NA 0.7501467 NA
     [1] "Surv est: 0.983758322675102"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=0: 0.01624"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -4.67474313 0.19724908 2.21184261 -0.09839186 0.76483183 0.36869687
     TI.tminus1
     -0.98759997
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.48082464 0.25283340 2.46508499 0.04786835 NA -0.43706261
     TI.tminus1
     NA
     [1] "Surv est: 0.969902221464484"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=1: 0.0301"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.8073588 -1.1071567 1.3574257 -0.4540453 0.6083749 0.3767599 -1.4726757
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7570081 -0.3346276 1.4801253 -0.3532999 0.5055449 -0.5127511 -0.6589153
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.90325161 -0.07708853 2.01607750 -0.02829320 NA -0.32644563
     TI.tminus1
     NA
     [1] "Surv est: 0.953782240282527"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=2: 0.04622"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.2729961 0.6045142 2.3185601 -1.4506484 0.4525435 -1.0902410 -1.7027505
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.45925760 -0.49121038 1.40054082 -0.35287095 0.50934192 -0.02283871
     TI.tminus1
     -1.28687470
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8442520 -0.1010111 1.5056775 -0.2372471 0.4546915 -0.4782690 -0.6244729
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.94053966 0.04857403 1.99765895 0.01058704 NA -0.32554792
     TI.tminus1
     NA
     [1] "Surv est: 0.953681572539541"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04632"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.0863662 1.4415952 1.1242617 -0.4941329 -0.1391926 -0.8298997 -0.6156850
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1883548 1.2010569 1.3144619 -0.3947993 0.1333006 -0.9913184 -0.5170650
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.11978976 0.36019767 1.14780785 -0.23837798 0.37263297 -0.05869163
     TI.tminus1
     -0.85675524
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.6602088 0.3624027 1.3288288 -0.1996436 0.3619692 -0.4185487 -0.4804042
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.757594710 0.346812991 1.758549008 0.002438552 NA -0.302239540
     TI.tminus1
     NA
     [1] "Surv est: 0.943575229684677"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.05642"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.694637 0.368584 3.290803 -0.666631 NA NA NA
     [1] "tmle update: -0.00149135496809919"
     [1] "Surv est: 0.984107401301778"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=0: 0.01589"
     [1] "...empirical mean of the estimated EIC: -3.09079900454493e-05"
     [1] "...estimated TMLE variance: 2.41999050417123e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8004930 0.9282348 0.6879804 -0.5514791 0.7438655 NA NA
     [1] "tmle update: 0.0727160966327068"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6000572 0.5722892 2.2618565 -0.7563574 NA NA NA
     [1] "tmle update: -0.0022357049164653"
     [1] "Surv est: 0.969834495012909"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=1: 0.03017"
     [1] "...empirical mean of the estimated EIC: -6.07101133764977e-05"
     [1] "...estimated TMLE variance: 6.61356670225727e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9817186 -17.2807447 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595614761723"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715771607933"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470300657529"
     [1] "Surv est: 0.951909613102674"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=2: 0.04809"
     [1] "...empirical mean of the estimated EIC: -0.00010436571628225"
     [1] "...estimated TMLE variance: 0.000251078927354862"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595625433471"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715771369513"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470300648418"
     [1] "Surv est: 0.95190961310293"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04809"
     [1] "...empirical mean of the estimated EIC: -0.000104365720571848"
     [1] "...estimated TMLE variance: 0.000251078927359577"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.209019147885717"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8958776 0.4984205 0.7750137 1.4400473 0.1142727 NA NA
     [1] "tmle update: 0.0520880449204392"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1879874 -0.3427790 0.1064457 -0.4879009 0.5164562 NA NA
     [1] "tmle update: -0.00448980897354264"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7827815 0.1202478 0.3514419 -0.6841186 0.4586810 NA NA
     [1] "tmle update: 0.0158905661689546"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.4482301 0.1976754 1.4967452 -0.5174974 NA NA NA
     [1] "tmle update: -0.00227377143477276"
     [1] "Surv est: 0.925542187707399"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.07446"
     [1] "...empirical mean of the estimated EIC: -0.000520790968265705"
     [1] "...estimated TMLE variance: 0.00803708770988044"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.0048959544125669"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715758304584"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470301977723"
     [1] "Surv est: 0.951909613112289"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04809"
     [1] "...empirical mean of the estimated EIC: -1.65538533979754e-05"
     [1] "...estimated TMLE variance: 8.3806787779791e-06"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.209019147869959"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8958776 0.4984205 0.7750137 1.4400473 0.1142727 NA NA
     [1] "tmle update: 0.0520880449202836"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1879874 -0.3427790 0.1064457 -0.4879009 0.5164562 NA NA
     [1] "tmle update: -0.00448980955099783"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7827815 0.1202478 0.3514419 -0.6841186 0.4586810 NA NA
     [1] "tmle update: 0.0158905661764066"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.4482301 0.1976754 1.4967452 -0.5174974 NA NA NA
     [1] "tmle update: -0.00227377139578826"
     [1] "Surv est: 0.925542187729508"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.07446"
     [1] "...empirical mean of the estimated EIC: -8.12433860103523e-05"
     [1] "...estimated TMLE variance: 0.00019629047768188"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: 0.00455038396959821"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5351943 -0.2698513 0.0819634 -1.1897532 1.1194722 NA NA
     [1] "tmle update: 0.00148791277372786"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.9037005 0.1316045 1.9048099 -0.7888752 NA NA NA
     [1] "tmle update: 0.0038737545211174"
     [1] "Surv est: 0.952423126954576"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04758"
     [1] "...empirical mean of the estimated EIC: -3.11352727229658e-05"
     [1] "...estimated TMLE variance: 4.05438882728483e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.0043556607594549"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -5.1065413 0.4996280 0.7537557 1.4595663 0.1268353 NA NA
     [1] "tmle update: -6.23198919478809e-11"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.365723662 -0.465839994 0.005840225 -0.509288785 0.596038204 NA
     TI.tminus1
     NA
     [1] "tmle update: -4.44506521637441e-10"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.88176714 0.08310961 0.32781298 -0.75064933 0.51647978 NA
     TI.tminus1
     NA
     [1] "tmle update: 5.99566016142493e-11"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.5397115 0.1898817 1.5664979 -0.5505100 NA NA NA
     [1] "tmle update: 0.0027933549293886"
     [1] "Surv est: 0.931389922902869"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.06861"
     [1] "...empirical mean of the estimated EIC: -3.04000131367507e-05"
     [1] "...estimated TMLE variance: 5.41527268962014e-05"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -2.240428e-13 -9.163027e-14
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -4.661343e-14 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.830025e-13 -7.964050e-14
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     1.2490429 NA -0.4673254 -0.1775312
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.03015004 NA NA 0.01124218 -0.01120127
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -4.661343e-14 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.830025e-13 -7.964050e-14
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     1.2490429 NA -0.4673254 -0.1775312
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.03015004 NA NA 0.01124218 -0.01120127
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     done successfully.
    
    
    
     Executing test function test.speedglm.allestimators10Kdata ... [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     writing report to directory: /tmp/RtmpJeyTeJ
     writing related figures to report subdirectory: figure.sim.data.example.fup2
    
    
     processing file: /tmp/RtmpJeyTeJ/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
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     $ results: chr "asis"
    
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     $ fig.width : num 5
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     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
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     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
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     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
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     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /tmp/RtmpJeyTeJ/report-script-rmd.knit.md
    
     /usr/local/bin/pandoc +RTS -K512m -RTS /tmp/RtmpJeyTeJ/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpJeyTeJ/sim.data.example.fup2.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /data/gannet/ripley/R/test-clang/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpJeyTeJ/rmarkdown-str320eb718198.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup2.html
     writing report to directory: /tmp/RtmpJeyTeJ
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpJeyTeJ/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
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     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
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     inline R code fragments
    
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     output file: /tmp/RtmpJeyTeJ/report-script-rmd.knit.md
    
     /usr/local/bin/pandoc +RTS -K512m -RTS /tmp/RtmpJeyTeJ/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpJeyTeJ/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /data/gannet/ripley/R/test-clang/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpJeyTeJ/rmarkdown-str320e3b52707.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpJeyTeJ
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpJeyTeJ/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
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     label: unnamed-chunk-1 (with options)
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     output file: /tmp/RtmpJeyTeJ/report-script-rmd.knit.md
    
     /usr/local/bin/pandoc +RTS -K512m -RTS /tmp/RtmpJeyTeJ/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpJeyTeJ/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /data/gannet/ripley/R/test-clang/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpJeyTeJ/rmarkdown-str320e7438339b.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpJeyTeJ
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpJeyTeJ/report-script-rmd.spin.Rmd
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     output file: /tmp/RtmpJeyTeJ/report-script-rmd.knit.md
    
     /usr/local/bin/pandoc +RTS -K512m -RTS /tmp/RtmpJeyTeJ/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpJeyTeJ/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /data/gannet/ripley/R/test-clang/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpJeyTeJ/rmarkdown-str320e3697e070.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpJeyTeJ
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpJeyTeJ/report-script-rmd.spin.Rmd
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     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
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     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
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     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
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     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /tmp/RtmpJeyTeJ/report-script-rmd.knit.md
    
     /usr/local/bin/pandoc +RTS -K512m -RTS /tmp/RtmpJeyTeJ/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpJeyTeJ/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /data/gannet/ripley/R/test-clang/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpJeyTeJ/rmarkdown-str320e49aecb5a.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpJeyTeJ
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpJeyTeJ/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
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     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
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     inline R code fragments
    
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     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
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     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
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     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
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     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /tmp/RtmpJeyTeJ/report-script-rmd.knit.md
    
     /usr/local/bin/pandoc +RTS -K512m -RTS /tmp/RtmpJeyTeJ/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpJeyTeJ/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /data/gannet/ripley/R/test-clang/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpJeyTeJ/rmarkdown-str320e6c1730a9.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpJeyTeJ
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpJeyTeJ/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
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     inline R code fragments
    
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     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
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     $ results: chr "asis"
    
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     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
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     inline R code fragments
    
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     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
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     $ echo : logi FALSE
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     ordinary text without R code
    
     output file: /tmp/RtmpJeyTeJ/report-script-rmd.knit.md
    
     /usr/local/bin/pandoc +RTS -K512m -RTS /tmp/RtmpJeyTeJ/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpJeyTeJ/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /data/gannet/ripley/R/test-clang/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpJeyTeJ/rmarkdown-str320e5f7ce089.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
    
    
     processing file: /tmp/RtmpJeyTeJ/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
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     $ echo : logi FALSE
     $ fig.width : num 5
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     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
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     inline R code fragments
    
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     inline R code fragments
    
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     label: unnamed-chunk-17 (with options)
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     label: unnamed-chunk-18 (with options)
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     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
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     output file: /tmp/RtmpJeyTeJ/report-script-rmd.knit.md
    
     /usr/local/bin/pandoc +RTS -K512m -RTS /tmp/RtmpJeyTeJ/report-script-rmd.utf8.md --to latex --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpJeyTeJ/sim.data.example.fup.tex --table-of-contents --toc-depth 2 --template /data/gannet/ripley/R/test-clang/rmarkdown/rmd/latex/default-1.17.0.2.tex --number-sections --highlight-style tango --latex-engine pdflatex --variable graphics=yes --variable 'geometry:margin=1in'
     You are recommended to install the tinytex package to build PDF.FALSE
     Latexmk: This is Latexmk, John Collins, 17 Jan. 2018, version: 4.55.
    
     Latexmk: No file name specified, and I couldn't find any
     Use
     latexmk -help
     to get usage information
    
     Output created: sim.data.example.fup.pdf
     Timing stopped at: 52.86 3.117 65.3
     Error in make_report_rmd(OData, NPMSM = list(surv1, surv2), MSM = MSM.IPAW, :
     file '/tmp/RtmpJeyTeJ/sim.data.example.fup.pdf' does not exist
     done successfully.
    
    
    
     Executing test function test.speedglm.stochastic.TMLE.NDE.1Kdata ... done successfully.
    
    
    
     Executing test function test.GCOMP.TMLE.10Kdata ... done successfully.
    
    
    
     Executing test function test.directRegressionDefn.10Kdata ... done successfully.
    
    
    
     Executing test function test.iterTMLE.10Kdata ... done successfully.
    
    
    
     Executing test function test.ContinModel ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "continA"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: continA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "ContinModel outcome: continA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: continA_B.1, continA_B.2, continA_B.3, continA_B.4, continA_B.5, continA_B.6, continA_B.7, continA_B.8, continA_B.9, continA_B.10, continA_B.11, continA_B.12, continA_B.13, continA_B.14, continA_B.15, continA_B.16, continA_B.17, continA_B.18, continA_B.19, continA_B.20, continA_B.21, continA_B.22, continA_B.23, continA_B.24, continA_B.25, continA_B.26, continA_B.27, continA_B.28, continA_B.29"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 29"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.4|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.5|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.6|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.7|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.8|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.9|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.10|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.11|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.12|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.13|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.14|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.15|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.16|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.17|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.18|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.19|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.20|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.21|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.22|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.23|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.24|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.25|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.26|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.27|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.28|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.29|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for continuous outcome: continA"
     [1] "freq counts by bin for continuous outcome: "
    
     2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
     519 518 518 518 518 518 518 518 518 518 518 518 518 519 518 518 518 518 518 518 518 518 518 518 518
     27 28
     518 519
     [1] "binned dataset: "
     continA_B.1 continA_B.2 continA_B.3 continA_B.4 continA_B.5 continA_B.6 continA_B.7
     [1,] 25 0 0 0 0 0 0 0
     [2,] 5 0 0 0 0 1 NA NA
     [3,] 16 0 0 0 0 0 0 0
     [4,] 10 0 0 0 0 0 0 0
     [5,] 25 0 0 0 0 0 0 0
     continA_B.8 continA_B.9 continA_B.10 continA_B.11 continA_B.12 continA_B.13 continA_B.14
     [1,] 0 0 0 0 0 0 0
     [2,] NA NA NA NA NA NA NA
     [3,] 0 0 0 0 0 0 0
     [4,] 0 0 1 NA NA NA NA
     [5,] 0 0 0 0 0 0 0
     continA_B.15 continA_B.16 continA_B.17 continA_B.18 continA_B.19 continA_B.20 continA_B.21
     [1,] 0 0 0 0 0 0 0
     [2,] NA NA NA NA NA NA NA
     [3,] 0 1 NA NA NA NA NA
     [4,] NA NA NA NA NA NA NA
     [5,] 0 0 0 0 0 0 0
     continA_B.22 continA_B.23 continA_B.24 continA_B.25 continA_B.26 continA_B.27 continA_B.28
     [1,] 0 0 0 1 NA NA NA
     [2,] NA NA NA NA NA NA NA
     [3,] NA NA NA NA NA NA NA
     [4,] NA NA NA NA NA NA NA
     [5,] 0 0 0 1 NA NA NA
     continA_B.29
     [1,] NA
     [2,] NA
     [3,] NA
     [4,] NA
     [5,] NA
     [1] "fitting the model: P(continA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.656607e+01 -1.172459e-11 -1.310221e-11 -2.568646e-11
     [1] "fitting the model: P(continA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.24647013 0.22219394 0.08440469 -0.10287396
     [1] "fitting the model: P(continA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.22055202 -0.12582015 0.10600998 -0.01409545
     [1] "fitting the model: P(continA_B.4|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.17594759 -0.01368306 -0.05907649 0.01988067
     [1] "fitting the model: P(continA_B.5|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.159478875 0.031913260 0.004704732 0.035985591
     [1] "fitting the model: P(continA_B.6|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.02413634 -0.31218774 -0.00911364 -0.06716957
     [1] "fitting the model: P(continA_B.7|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.006157367 -0.007196951 0.141151721 -0.129264428
     [1] "fitting the model: P(continA_B.8|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.08132353 0.09622253 -0.02571364 0.14388155
     [1] "fitting the model: P(continA_B.9|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.954860665 0.009740307 0.060867275 -0.005863002
     [1] "fitting the model: P(continA_B.10|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.883062037 -0.102809789 0.007781733 0.003276532
     [1] "fitting the model: P(continA_B.11|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.78913918 -0.21162028 -0.11541024 -0.00171932
     [1] "fitting the model: P(continA_B.12|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.80983797 0.26006995 -0.15457377 0.06218821
     [1] "fitting the model: P(continA_B.13|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.62858816 0.00572836 -0.03705326 -0.14115055
     [1] "fitting the model: P(continA_B.14|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.63665823 0.06625965 0.17506973 -0.08951695
     [1] "fitting the model: P(continA_B.15|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.51851485 0.13723137 0.04260153 -0.13174946
     [1] "fitting the model: P(continA_B.16|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.43780463 -0.03256695 -0.14039333 -0.03242460
     [1] "fitting the model: P(continA_B.17|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.39851433 -0.04034581 0.06257761 -0.01482731
     [1] "fitting the model: P(continA_B.18|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.33285222 0.03980025 0.03265581 0.03522587
     [1] "fitting the model: P(continA_B.19|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.15663768 -0.24041036 0.01148885 -0.03589220
     [1] "fitting the model: P(continA_B.20|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.01441787 0.09806226 -0.32369388 -0.03553421
     [1] "fitting the model: P(continA_B.21|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.031346340 0.034296762 -0.004591859 0.148267985
     [1] "fitting the model: P(continA_B.22|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.81009128 -0.15873563 -0.08020680 0.09243934
     [1] "fitting the model: P(continA_B.23|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.65296095 -0.10161850 0.05299547 0.07966687
     [1] "fitting the model: P(continA_B.24|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.42606832 0.13276531 -0.04202152 0.06031588
     [1] "fitting the model: P(continA_B.25|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.02895731 -0.05049212 -0.17370121 -0.05851172
     [1] "fitting the model: P(continA_B.26|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -0.77074301 0.33532831 0.10512888 0.02896302
     [1] "fitting the model: P(continA_B.27|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.01363815 -0.04799168 0.22938334 -0.10942815
     [1] "fitting the model: P(continA_B.28|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656607e+01 -4.743500e-06 1.281238e-07 3.470967e-09
     [1] "fitting the model: P(continA_B.29|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for outcome continA succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for continuous outcome: continA"
     [1] "performing prediction for continuous outcome: continA"
     done successfully.
    
     ------------------- UNIT TEST SUMMARY ---------------------
    
     RUNIT TEST PROTOCOL -- Sat Apr 14 10:28:58 2018
     ***********************************************
     Number of test functions: 18
     Number of errors: 1
     Number of failures: 0
    
    
     1 Test Suite :
     stremr unit testing - 18 test functions, 1 error, 0 failures
     ERROR in test.speedglm.allestimators10Kdata: Error in make_report_rmd(OData, NPMSM = list(surv1, surv2), MSM = MSM.IPAW, :
     file '/tmp/RtmpJeyTeJ/sim.data.example.fup.pdf' does not exist
     Error:
    
     unit testing failed (#test failures: 0, #R errors: 1)
    
     Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang

Version: 0.4
Check: tests
Result: ERROR
     Running ‘test-all.R’ [154s/169s]
    Running the tests in ‘tests/test-all.R’ failed.
    Complete output:
     > ## unit tests will not be done if RUnit is not available
     > # setwd("..")
     > # getwd()
     > # library(RUnit)
     > if(require("RUnit", quietly=TRUE)) {
     + ## --- Setup ---
     +
     + pkg <- "stremr" # <-- Tested package name
     +
     + if(Sys.getenv("RCMDCHECK") == "FALSE") {
     + ## Path to unit tests for standalone running under Makefile (not R CMD check)
     + ## PKG/tests/../inst/unitTests
     + # path <- file.path(getwd(), "..", "inst", "unitTests")
     + } else {
     + ## Path to unit tests for R CMD check
     + ## PKG.Rcheck/tests/../PKG/unitTests
     + # path <- system.file(package=pkg, "RUnit")
     +
     + # REPLACED WITH:
     + path <- file.path(getwd(), "RUnit")
     + }
     +
     + cat("\nRunning unit tests\n")
     + print(list(pkg=pkg, getwd=getwd(), pathToUnitTests=path))
     +
     + library(package=pkg, character.only=TRUE)
     +
     + ## If desired, load the name space to allow testing of private functions
     + ## if (is.element(pkg, loadedNamespaces()))
     + ## attach(loadNamespace(pkg), name=paste("namespace", pkg, sep=":"), pos=3)
     + ##
     + ## or simply call PKG:::myPrivateFunction() in tests
     +
     + ## --- Testing ---
     +
     + ## Define tests
     + test.suite <- defineTestSuite(name=paste(pkg, "unit testing"),
     + # dirs="./RUnit",
     + dirs=path,
     + testFileRegexp = "^RUnit_tests_+",
     + testFuncRegexp = "^test.+",
     + rngKind = "Marsaglia-Multicarry",
     + rngNormalKind = "Kinderman-Ramage")
     + ## Run
     + tests <- runTestSuite(test.suite)
     +
     + ## Default report name
     + pathReport <- file.path(path, "report")
     +
     + ## Report to stdout and text files
     + cat("------------------- UNIT TEST SUMMARY ---------------------\n\n")
     + printTextProtocol(tests, showDetails=FALSE)
     + printTextProtocol(tests, showDetails=FALSE,
     + fileName=paste0(pathReport, "Summary.txt"))
     + printTextProtocol(tests, showDetails=TRUE,
     + fileName=paste0(pathReport, ".txt"))
     + ## Report to HTML file
     + printHTMLProtocol(tests, fileName=paste0(pathReport, ".html"))
     +
     + ## Return stop() to cause R CMD check stop in case of
     + ## - failures i.e. FALSE to unit tests or
     + ## - errors i.e. R errors
     + tmp <- getErrors(tests)
     + if(tmp$nFail > 0 | tmp$nErr > 0) {
     + stop(paste("\n\nunit testing failed (#test failures: ", tmp$nFail,
     + ", #R errors: ", tmp$nErr, ")\n\n", sep=""))
     + }
     + } else {
     + warning("cannot run unit tests -- package RUnit is not available")
     + }
    
     Running unit tests
     $pkg
     [1] "stremr"
    
     $getwd
     [1] "/data/gannet/ripley/R/packages/tests-devel/stremr.Rcheck/tests"
    
     $pathToUnitTests
     [1] "/data/gannet/ripley/R/packages/tests-devel/stremr.Rcheck/tests/RUnit"
    
    
    
     Executing test function test.GenericModelPredict ... Loading required package: data.table
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.6829138 1.4512950 -0.4353432 0.5852046
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "catA"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: catA"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA, catA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "CategorModel outcome: catA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA_B.1, catA_B.2, catA_B.3"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "CategorModel outcome: catA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA_B.1, catA_B.2, catA_B.3"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for outcome based on stratified model for outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: catA"
     [1] "freq counts by bin for categorical outcome: "
    
     1 2 3
     4642 4736 4611
     [1] "binned dataset: "
     sA catA_B.1 catA_B.2 catA_B.3
     [1,] 3 NA 1 NA
     [2,] 1 NA 1 NA
     [3,] 2 NA 1 NA
     [4,] 3 NA 1 NA
     [5,] 3 NA 1 NA
     [1] "fitting the model: P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     [1] "fitting the model: P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -9.762950e-08 2.155173e-06 NA
     [1] "fitting the model: P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for catA var succeeded...
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: catA"
     [1] "freq counts by bin for categorical outcome: "
    
     1 2 3
     4642 4736 4611
     [1] "binned dataset: "
     sA catA_B.1 catA_B.2 catA_B.3
     [1,] 3 NA 1 NA
     [2,] 1 NA 1 NA
     [3,] 2 NA 1 NA
     [4,] 3 NA 1 NA
     [5,] 3 NA 1 NA
     [1] "fitting the model: P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     [1] "fitting the model: P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -3.738646e-08 -2.346217e-07 -2.013073e-07
     [1] "fitting the model: P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for catA var succeeded...
     fit for catA var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: catA"
     [1] "performing prediction for categorical outcome: catA"
     [1] "performing prediction for categorical outcome: catA"
     [1] "performing prediction for outcome based on stratified model: catA"
     [1] "performing prediction for categorical outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing prediction for categorical outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     done successfully.
    
    
    
     Executing test function test.Nsamp.n.test ... done successfully.
    
    
    
     Executing test function test.options ... [1] "Possible `stremr` options:"
     [1] "fit.package" "fit.algorithm" "bin.method"
     [4] "nbins" "maxncats" "maxNperBin"
     [7] "lower_bound_zero_Q" "skip_update_zero_Q"
     Error in stremrOptions("blahblah") :
     blahblah: this options does not exist
     Error in stremrOptions("blahblah", 5) : Invalid option name: blahblah
     Error in if (!(fit.algorithm %in% allowed.fit.algorithm)) stop("fit.algorithm must be one of: " %+% :
     argument is of length zero
     Error in set_all_stremr_options(fit.package = "speedglm", fit.algorithm = "blahblah", :
     fit.algorithm must be one of: glm, gbm, randomForest, deeplearning
     Error in set_all_stremr_options(fit.package = "blahblah", fit.algorithm = "glm", :
     fit.package must be one of: speedglm, glm, h2o
     Error in set_all_stremr_options(fit.package = "speedglm", fit.algorithm = "glm", :
     bin.method must be one of: equal.mass, equal.len, dhist
     $fit.package
     [1] "speedglm"
    
     $fit.algorithm
     [1] "glm"
    
     $bin.method
     [1] "equal.mass"
    
     $nbins
     [1] 10
    
     $maxncats
     [1] 20
    
     $maxNperBin
     [1] 500
    
     $lower_bound_zero_Q
     [1] TRUE
    
     $skip_update_zero_Q
     [1] TRUE
    
     done successfully.
    
    
    
     Executing test function test.regressionCases ... done successfully.
    
    
    
     Executing test function test.t.error ... done successfully.
    
    
    
     Executing test function test.DataStorageClass ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     Error in OData$get.outvar(var = "blah") :
     requested variable blah does not exist in DataStorageClass!
     done successfully.
    
    
    
     Executing test function test.error.fits.stratify ... Error in create_subset_expr(outvars = res$outvars, stratify.EXPRS = stratify.EXPRS) :
     Could not locate the appropriate regression variable(s) within the supplied stratification list stratify_CENS, stratify_TRT or stratify_MONITOR.
     The regression outcome variable(s) specified in gform_CENS, gform_TRT or gform_MONITOR were: ( 'C,TI' )
     However, the item names in the matching stratification list were: ( 'wrongC,TI,N' )
     done successfully.
    
    
    
     Executing test function test.helperfuns ... done successfully.
    
    
    
     Executing test function test.model.fits.stratify ... done successfully.
    
    
    
     Executing test function test.model.fits.categorCENSOR ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.52652066 0.05456581 0.10858685
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.19067146 NA 0.43343872 -0.01789425
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01340964 NA NA -0.03245807 -0.01185101
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 8.599825e-13 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.29183433 -0.07998923 0.03081559
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.64534186 NA 0.09366241 -0.16923766
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01135495 NA NA -0.02269938 -0.01321850
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 1,t > 0 & C == 1)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 1"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 1"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 1 & TI == 1,t > 0 & C == 1 & TI == 1)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 1 & TI == 1"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 1 & TI == 1"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 8.599825e-13 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.29183433 -0.07998923 0.03081559
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     NA NA NA NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     NA 0.4924641 0.1270091 -0.1911502
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 1 & TI == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     NA NA NA NA NA
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 1 & TI == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     NA NA NA NA NA
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,t > 0L & TI.tminus1 == 0L,t > 0L & TI.tminus1 == 1L)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 1L"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.52652066 0.05456581 0.10858685
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.64534186 NA 0.09366241 -0.16923766
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     -0.01467019 -0.45533330 NA NA NA
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     -0.01135495 -0.02269938 -0.01321850 NA NA
     fit for N var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -21.2548627 0.9100488 2.1714524 19.1407169
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 1L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 1.092843e-07 1.158713e-07 1.320318e-07
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "performing prediction for outcome based on stratified model: TI"
     done successfully.
    
    
    
     Executing test function test.model.fits.categorCENSOR2 ... Loading required package: magrittr
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "CatC"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: CatC"
     [1] "StratifiedModel expressions: (t < 16,t == 16)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC, CatC"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     ...fitting a model for categorical censoring...
     [1] "CategorModel outcome: CatC"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC_B.1, CatC_B.2, CatC_B.3"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.1|highA1c);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.2|highA1c);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.3|highA1c);\\ Stratify: t < 16"
     ...fitting a model for categorical censoring...
     [1] "CategorModel outcome: CatC"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC_B.1, CatC_B.2, CatC_B.3"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.1|highA1c);\\ Stratify: t == 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.2|highA1c);\\ Stratify: t == 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.3|highA1c);\\ Stratify: t == 16"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,(t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L),(t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L),(t > 0L) & (barTIm1eq0 == 1L))"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI, TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L)"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L)"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (barTIm1eq0 == 1L)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: CatC"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: CatC"
     [1] "freq counts by bin for categorical outcome: "
    
     0 1 2
     7469 347 314
     [1] "binned dataset: "
     sA CatC_B.1 CatC_B.2 CatC_B.3
     [1,] 0 0 0 NA
     [2,] 0 0 0 NA
     [3,] 1 1 NA NA
     [4,] 0 0 0 NA
     [5,] 0 0 0 NA
     [1] "fitting the model: P(CatC_B.1|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -3.1487960 0.1616531
     [1] "fitting the model: P(CatC_B.2|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -3.13719779 -0.08098814
     [1] "fitting the model: P(CatC_B.3|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     NA NA
     fit for CatC var succeeded...
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: CatC"
     [1] "freq counts by bin for categorical outcome: "
    
     0 1 2
     7469 347 314
     [1] "binned dataset: "
     sA CatC_B.1 CatC_B.2 CatC_B.3
     [1,] 0 0 0 NA
     [2,] 0 0 0 NA
     [3,] 1 1 NA NA
     [4,] 0 0 0 NA
     [5,] 0 0 0 NA
     [1] "fitting the model: P(CatC_B.1|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -2.9593646 0.5614693
     [1] "fitting the model: P(CatC_B.2|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -4.89784 -15.66823
     [1] "fitting the model: P(CatC_B.3|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     NA NA
     fit for CatC var succeeded...
     fit for CatC var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.1141458 0.9100488 2.1714524 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.656607e+01 2.444839e-12 2.082888e-12 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -21.2548627 0.9100488 2.1714524 19.1407169
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: CatC"
     [1] "performing prediction for categorical outcome: CatC"
     [1] "performing prediction for categorical outcome: CatC"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "N"
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     done successfully.
    
    
    
     Executing test function test.buildingblocks ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     Error in getIPWeights(OData = OData, intervened_TRT = "TI.set1", rule_name = "TI1") :
     ...cannot locate propensity scores in 'OData' object - must run fitPropensity(...) prior to calling this function
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t < 16,t == 16)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 16"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t < 16"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.198768e-13 -5.125570e-14
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 16"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -6.143963e-14 -2.839781e-14
     fit for C var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "performing estimation for the following TRT/MONITOR rules found in column 'rule.name': TI0,TI1"
     [1] "periods"
     [1] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
     [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     [1] "Periods.0to0_TI0"
     [1] "Periods.1to1_TI0"
     [1] "Periods.2to2_TI0"
     [1] "Periods.3to3_TI0"
     [1] "Periods.4to4_TI0"
     [1] "Periods.5to5_TI0"
     [1] "Periods.6to6_TI0"
     [1] "Periods.7to7_TI0"
     [1] "Periods.8to11_TI0"
     [1] "Periods.12to15_TI0"
     [1] "Periods.0to0_TI1"
     [1] "Periods.1to1_TI1"
     [1] "Periods.2to2_TI1"
     [1] "Periods.3to3_TI1"
     [1] "Periods.4to4_TI1"
     [1] "Periods.5to5_TI1"
     [1] "Periods.6to6_TI1"
     [1] "Periods.7to7_TI1"
     [1] "Periods.8to11_TI1"
     [1] "Periods.12to15_TI1"
     ...fitting hazard MSM with speedglm::speedglm.wfit...
     [1] "MSM fits"
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     -5.465039e+00 -4.324378e+00 -4.012934e+00 -1.166619e+15
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     -6.871355e+14 -4.884654e+14 -6.732368e+00 -6.414551e+00
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     -2.490327e+15 -3.057464e+15 -3.089228e+00 -4.070768e+00
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     -4.097356e+00 -1.444049e+01 -3.626218e+00 -4.172158e+00
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     -5.928687e+00 -3.921940e+00 -4.645602e+00 -3.410729e+00
     ...evaluating MSM-based survival curves...
     ...evaluating SEs based on MSM hazard fit and the estimated IC...
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     9.379699e-17 2.900859e-16 7.383396e-15 7.293270e+00
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     6.561300e+01 4.445403e+02 3.220105e-14 2.800474e-14
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.030033e+02 7.899748e+02 7.913397e-18 2.865011e-18
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     7.009244e-18 4.879654e-08 1.399031e-19 7.292022e-18
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     2.532557e-18 1.471364e-17 3.615109e-16 1.717254e-15
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     9.340525e-15 3.126553e-15 1.800440e-14 3.336980e+14
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     7.563694e+14 1.183848e+15 5.560005e-15 5.426432e-15
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     1.830248e+14 5.408850e+14 4.968619e-15 3.569094e-15
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     6.622362e-15 1.000001e+00 8.253617e-17 2.682887e-15
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     3.708932e-15 2.085976e-15 9.255499e-15 3.032843e-15
     [1] "Should all be very small: "
     [1] 3.953818e-17 7.916801e-17 2.288376e-16 2.288376e-16 2.288376e-16
     [6] 2.288376e-16 2.227361e-16 2.339417e-16 2.339417e-16 2.339417e-16
     [11] 2.339417e-16 2.339417e-16 2.339417e-16 2.339417e-16 2.339417e-16
     [16] 2.339417e-16
     [1] "Should all be very small: "
     [1] 2.087237e-16 2.567391e-16 1.552191e-16 4.951408e-07 4.823035e-07
     [6] 4.749798e-07 4.737188e-07 4.645200e-07 4.601013e-07 4.557247e-07
     [11] 4.513896e-07 4.470959e-07 4.328058e-07 4.189726e-07 4.055814e-07
     [16] 3.926183e-07
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -2.240428e-13 -9.163027e-14
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "performing estimation for the following TRT/MONITOR rules found in column 'rule.name': TI0,TI1"
     [1] "periods"
     [1] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
     [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     [1] "Periods.0to0_TI0"
     [1] "Periods.1to1_TI0"
     [1] "Periods.2to2_TI0"
     [1] "Periods.3to3_TI0"
     [1] "Periods.4to4_TI0"
     [1] "Periods.5to5_TI0"
     [1] "Periods.6to6_TI0"
     [1] "Periods.7to7_TI0"
     [1] "Periods.8to11_TI0"
     [1] "Periods.12to15_TI0"
     [1] "Periods.0to0_TI1"
     [1] "Periods.1to1_TI1"
     [1] "Periods.2to2_TI1"
     [1] "Periods.3to3_TI1"
     [1] "Periods.4to4_TI1"
     [1] "Periods.5to5_TI1"
     [1] "Periods.6to6_TI1"
     [1] "Periods.7to7_TI1"
     [1] "Periods.8to11_TI1"
     [1] "Periods.12to15_TI1"
     ...fitting hazard MSM with speedglm::speedglm.wfit...
     [1] "MSM fits"
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     -5.479625e+00 -4.224521e+15 -4.040682e+15 -3.195295e+15
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     -3.082898e+15 -2.778817e+15 -3.052026e+15 -3.796228e+15
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     -2.715406e+15 -1.534193e+15 -3.048470e+00 -4.020852e+00
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     -4.106498e+00 -1.007712e+01 -3.450746e+00 -4.160778e+00
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     -5.909203e+00 -4.008647e+00 -4.781623e+00 -3.422484e+15
     ...evaluating MSM-based survival curves...
     ...evaluating SEs based on MSM hazard fit and the estimated IC...
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     1.363995e-15 3.892340e+00 1.153066e+02 3.014492e+03
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     2.096739e+04 2.100000e+04 1.300000e+04 5.000000e+03
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.700000e+04 1.000000e+04 2.218218e-17 1.992734e-17
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     1.087903e-17 1.670762e-05 2.380815e-17 8.984546e-17
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     4.050727e-18 8.676045e-17 3.446043e-04 2.159757e+02
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     2.012238e-14 5.581563e+13 7.715289e+13 2.180508e+14
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     2.367837e+14 2.874638e+14 2.419289e+14 1.178953e+14
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.980323e+14 4.949011e+14 9.314984e-15 1.161900e-14
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     3.404072e-15 1.000042e+00 9.042079e-16 3.580885e-15
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     4.712621e-16 6.766642e-16 1.571325e-04 1.801860e+14
     [1] "Should all be very small: "
     [1] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [6] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [11] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [16] 8.330934e-17
     [1] "Should all be very small: "
     [1] 3.999902e-16 2.024836e-16 2.525296e-16 3.877971e-05 3.758736e-05
     [6] 3.701017e-05 3.690999e-05 3.625173e-05 3.706763e-05 3.786745e-05
     [11] 3.865142e-05 3.941974e-05 3.941974e-05 3.941974e-05 3.941974e-05
     [16] 3.941974e-05
     Error in process_opt_wts(wts_data_used, weights, nodes) :
     input 'weights' must be a data.table with 3 columns, two of which must be named as: 'ID' and 't'.
     In addition: Warning messages:
     1: glm.fit: algorithm did not converge
     2: glm.fit: algorithm did not converge
     3: glm.fit: algorithm did not converge
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -5.8682574 0.2154351 3.3021509 0.4033691 NA 0.7501467 NA
     [1] "Surv est: 0.983758322675102"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=0: 0.01624"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -4.67474313 0.19724908 2.21184261 -0.09839186 0.76483183 0.36869687
     TI.tminus1
     -0.98759997
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.48082464 0.25283340 2.46508499 0.04786835 NA -0.43706261
     TI.tminus1
     NA
     [1] "Surv est: 0.969902221464484"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=1: 0.0301"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.8073588 -1.1071567 1.3574257 -0.4540453 0.6083749 0.3767599 -1.4726757
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7570081 -0.3346276 1.4801253 -0.3532999 0.5055449 -0.5127511 -0.6589153
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.90325161 -0.07708853 2.01607750 -0.02829320 NA -0.32644563
     TI.tminus1
     NA
     [1] "Surv est: 0.953782240282527"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=2: 0.04622"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.2729961 0.6045142 2.3185601 -1.4506484 0.4525435 -1.0902410 -1.7027505
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.45925760 -0.49121038 1.40054082 -0.35287095 0.50934192 -0.02283871
     TI.tminus1
     -1.28687470
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8442520 -0.1010111 1.5056775 -0.2372471 0.4546915 -0.4782690 -0.6244729
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.94053966 0.04857403 1.99765895 0.01058704 NA -0.32554792
     TI.tminus1
     NA
     [1] "Surv est: 0.953681572539541"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04632"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.0863662 1.4415952 1.1242617 -0.4941329 -0.1391926 -0.8298997 -0.6156850
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1883548 1.2010569 1.3144619 -0.3947993 0.1333006 -0.9913184 -0.5170650
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.11978976 0.36019767 1.14780785 -0.23837798 0.37263297 -0.05869163
     TI.tminus1
     -0.85675524
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.6602088 0.3624027 1.3288288 -0.1996436 0.3619692 -0.4185487 -0.4804042
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.757594710 0.346812991 1.758549008 0.002438552 NA -0.302239540
     TI.tminus1
     NA
     [1] "Surv est: 0.943575229684677"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.05642"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.694637 0.368584 3.290803 -0.666631 NA NA NA
     [1] "tmle update: -0.00149135496809919"
     [1] "Surv est: 0.984107401301778"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=0: 0.01589"
     [1] "...empirical mean of the estimated EIC: -3.09079900454493e-05"
     [1] "...estimated TMLE variance: 2.41999050417123e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8004930 0.9282348 0.6879804 -0.5514791 0.7438655 NA NA
     [1] "tmle update: 0.0727160966327068"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6000572 0.5722892 2.2618565 -0.7563574 NA NA NA
     [1] "tmle update: -0.0022357049164653"
     [1] "Surv est: 0.969834495012909"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=1: 0.03017"
     [1] "...empirical mean of the estimated EIC: -6.07101133764977e-05"
     [1] "...estimated TMLE variance: 6.61356670225727e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9817186 -17.2807447 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595614761723"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715771607933"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470300657529"
     [1] "Surv est: 0.951909613102674"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=2: 0.04809"
     [1] "...empirical mean of the estimated EIC: -0.00010436571628225"
     [1] "...estimated TMLE variance: 0.000251078927354862"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595625433471"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715771369513"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470300648418"
     [1] "Surv est: 0.95190961310293"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04809"
     [1] "...empirical mean of the estimated EIC: -0.000104365720571848"
     [1] "...estimated TMLE variance: 0.000251078927359577"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.209019147885717"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8958776 0.4984205 0.7750137 1.4400473 0.1142727 NA NA
     [1] "tmle update: 0.0520880449204392"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1879874 -0.3427790 0.1064457 -0.4879009 0.5164562 NA NA
     [1] "tmle update: -0.00448980897354264"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7827815 0.1202478 0.3514419 -0.6841186 0.4586810 NA NA
     [1] "tmle update: 0.0158905661689546"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.4482301 0.1976754 1.4967452 -0.5174974 NA NA NA
     [1] "tmle update: -0.00227377143477276"
     [1] "Surv est: 0.925542187707399"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.07446"
     [1] "...empirical mean of the estimated EIC: -0.000520790968265705"
     [1] "...estimated TMLE variance: 0.00803708770988044"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.0048959544125669"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715758304584"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470301977723"
     [1] "Surv est: 0.951909613112289"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04809"
     [1] "...empirical mean of the estimated EIC: -1.65538533979754e-05"
     [1] "...estimated TMLE variance: 8.3806787779791e-06"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.209019147869959"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8958776 0.4984205 0.7750137 1.4400473 0.1142727 NA NA
     [1] "tmle update: 0.0520880449202836"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1879874 -0.3427790 0.1064457 -0.4879009 0.5164562 NA NA
     [1] "tmle update: -0.00448980955099783"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7827815 0.1202478 0.3514419 -0.6841186 0.4586810 NA NA
     [1] "tmle update: 0.0158905661764066"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.4482301 0.1976754 1.4967452 -0.5174974 NA NA NA
     [1] "tmle update: -0.00227377139578826"
     [1] "Surv est: 0.925542187729508"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.07446"
     [1] "...empirical mean of the estimated EIC: -8.12433860103523e-05"
     [1] "...estimated TMLE variance: 0.00019629047768188"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: 0.00455038396959821"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5351943 -0.2698513 0.0819634 -1.1897532 1.1194722 NA NA
     [1] "tmle update: 0.00148791277372786"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.9037005 0.1316045 1.9048099 -0.7888752 NA NA NA
     [1] "tmle update: 0.0038737545211174"
     [1] "Surv est: 0.952423126954576"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04758"
     [1] "...empirical mean of the estimated EIC: -3.11352727229658e-05"
     [1] "...estimated TMLE variance: 4.05438882728483e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.0043556607594549"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -5.1065413 0.4996280 0.7537557 1.4595663 0.1268353 NA NA
     [1] "tmle update: -6.23198919478809e-11"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.365723662 -0.465839994 0.005840225 -0.509288785 0.596038204 NA
     TI.tminus1
     NA
     [1] "tmle update: -4.44506521637441e-10"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.88176714 0.08310961 0.32781298 -0.75064933 0.51647978 NA
     TI.tminus1
     NA
     [1] "tmle update: 5.99566016142493e-11"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.5397115 0.1898817 1.5664979 -0.5505100 NA NA NA
     [1] "tmle update: 0.0027933549293886"
     [1] "Surv est: 0.931389922902869"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.06861"
     [1] "...empirical mean of the estimated EIC: -3.04000131367507e-05"
     [1] "...estimated TMLE variance: 5.41527268962014e-05"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -2.240428e-13 -9.163027e-14
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -4.661343e-14 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.830025e-13 -7.964050e-14
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     1.2490429 NA -0.4673254 -0.1775312
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.03015004 NA NA 0.01124218 -0.01120127
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -4.661343e-14 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.830025e-13 -7.964050e-14
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     1.2490429 NA -0.4673254 -0.1775312
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.03015004 NA NA 0.01124218 -0.01120127
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     done successfully.
    
    
    
     Executing test function test.speedglm.allestimators10Kdata ... [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     writing report to directory: /tmp/RtmpYMYKLT
     writing related figures to report subdirectory: figure.sim.data.example.fup2
    
    
     processing file: /tmp/RtmpYMYKLT/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
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     $ include: logi FALSE
    
     inline R code fragments
    
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     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
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     $ results: chr "asis"
    
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     inline R code fragments
    
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     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
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     $ results: chr "asis"
    
     inline R code fragments
    
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     List of 4
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     $ fig.width : num 5
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     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
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     List of 1
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     $ fig.width : num 5
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     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
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     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
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     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
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     output file: /tmp/RtmpYMYKLT/report-script-rmd.knit.md
    
     /usr/local/bin/pandoc +RTS -K512m -RTS /tmp/RtmpYMYKLT/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpYMYKLT/sim.data.example.fup2.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /data/gannet/ripley/R/test-3.6/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpYMYKLT/rmarkdown-str7e1867a00400.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup2.html
     writing report to directory: /tmp/RtmpYMYKLT
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpYMYKLT/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
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     $ include: logi FALSE
    
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     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
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     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
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     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
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     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
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     $ echo : logi FALSE
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     ordinary text without R code
    
     output file: /tmp/RtmpYMYKLT/report-script-rmd.knit.md
    
     /usr/local/bin/pandoc +RTS -K512m -RTS /tmp/RtmpYMYKLT/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpYMYKLT/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /data/gannet/ripley/R/test-3.6/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpYMYKLT/rmarkdown-str7e1833464bbc.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpYMYKLT
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpYMYKLT/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-3 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-4 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     label: unnamed-chunk-5 (with options)
     List of 1
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-7 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-8 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-9 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /tmp/RtmpYMYKLT/report-script-rmd.knit.md
    
     /usr/local/bin/pandoc +RTS -K512m -RTS /tmp/RtmpYMYKLT/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpYMYKLT/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /data/gannet/ripley/R/test-3.6/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpYMYKLT/rmarkdown-str7e1810caf39e.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpYMYKLT
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpYMYKLT/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-3 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-4 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     label: unnamed-chunk-5 (with options)
     List of 1
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-7 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-8 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-9 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /tmp/RtmpYMYKLT/report-script-rmd.knit.md
    
     /usr/local/bin/pandoc +RTS -K512m -RTS /tmp/RtmpYMYKLT/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpYMYKLT/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /data/gannet/ripley/R/test-3.6/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpYMYKLT/rmarkdown-str7e182dbb7dcc.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpYMYKLT
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpYMYKLT/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-3 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-4 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     label: unnamed-chunk-5 (with options)
     List of 1
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-7 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-8 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-9 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /tmp/RtmpYMYKLT/report-script-rmd.knit.md
    
     /usr/local/bin/pandoc +RTS -K512m -RTS /tmp/RtmpYMYKLT/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpYMYKLT/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /data/gannet/ripley/R/test-3.6/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpYMYKLT/rmarkdown-str7e183643bb87.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpYMYKLT
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpYMYKLT/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-3 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-4 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     label: unnamed-chunk-5 (with options)
     List of 1
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-7 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-8 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-9 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /tmp/RtmpYMYKLT/report-script-rmd.knit.md
    
     /usr/local/bin/pandoc +RTS -K512m -RTS /tmp/RtmpYMYKLT/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpYMYKLT/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /data/gannet/ripley/R/test-3.6/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpYMYKLT/rmarkdown-str7e18535bc397.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpYMYKLT
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpYMYKLT/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-3 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-4 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     label: unnamed-chunk-5 (with options)
     List of 1
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-7 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-8 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-9 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /tmp/RtmpYMYKLT/report-script-rmd.knit.md
    
     /usr/local/bin/pandoc +RTS -K512m -RTS /tmp/RtmpYMYKLT/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpYMYKLT/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /data/gannet/ripley/R/test-3.6/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpYMYKLT/rmarkdown-str7e18591424d4.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
    
    
     processing file: /tmp/RtmpYMYKLT/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-3 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-4 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     label: unnamed-chunk-5 (with options)
     List of 1
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-7 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-8 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-9 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /tmp/RtmpYMYKLT/report-script-rmd.knit.md
    
     /usr/local/bin/pandoc +RTS -K512m -RTS /tmp/RtmpYMYKLT/report-script-rmd.utf8.md --to latex --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpYMYKLT/sim.data.example.fup.tex --table-of-contents --toc-depth 2 --template /data/gannet/ripley/R/test-3.6/rmarkdown/rmd/latex/default-1.17.0.2.tex --number-sections --highlight-style tango --latex-engine pdflatex --variable graphics=yes --variable 'geometry:margin=1in'
     You are recommended to install the tinytex package to build PDF.FALSE
     Latexmk: This is Latexmk, John Collins, 17 Jan. 2018, version: 4.55.
    
     Latexmk: No file name specified, and I couldn't find any
     Use
     latexmk -help
     to get usage information
    
     Output created: sim.data.example.fup.pdf
     Timing stopped at: 50.33 3.177 59.47
     Error in make_report_rmd(OData, NPMSM = list(surv1, surv2), MSM = MSM.IPAW, :
     file '/tmp/RtmpYMYKLT/sim.data.example.fup.pdf' does not exist
     done successfully.
    
    
    
     Executing test function test.speedglm.stochastic.TMLE.NDE.1Kdata ... done successfully.
    
    
    
     Executing test function test.GCOMP.TMLE.10Kdata ... done successfully.
    
    
    
     Executing test function test.directRegressionDefn.10Kdata ... done successfully.
    
    
    
     Executing test function test.iterTMLE.10Kdata ... done successfully.
    
    
    
     Executing test function test.ContinModel ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "continA"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: continA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "ContinModel outcome: continA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: continA_B.1, continA_B.2, continA_B.3, continA_B.4, continA_B.5, continA_B.6, continA_B.7, continA_B.8, continA_B.9, continA_B.10, continA_B.11, continA_B.12, continA_B.13, continA_B.14, continA_B.15, continA_B.16, continA_B.17, continA_B.18, continA_B.19, continA_B.20, continA_B.21, continA_B.22, continA_B.23, continA_B.24, continA_B.25, continA_B.26, continA_B.27, continA_B.28, continA_B.29"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 29"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.4|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.5|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.6|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.7|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.8|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.9|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.10|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.11|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.12|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.13|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.14|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.15|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.16|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.17|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.18|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.19|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.20|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.21|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.22|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.23|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.24|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.25|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.26|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.27|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.28|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.29|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for continuous outcome: continA"
     [1] "freq counts by bin for continuous outcome: "
    
     2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
     519 518 518 518 518 518 518 518 518 518 518 518 518 519 518 518 518 518 518 518 518 518 518 518 518
     27 28
     518 519
     [1] "binned dataset: "
     continA_B.1 continA_B.2 continA_B.3 continA_B.4 continA_B.5 continA_B.6 continA_B.7
     [1,] 24 0 0 0 0 0 0 0
     [2,] 24 0 0 0 0 0 0 0
     [3,] 14 0 0 0 0 0 0 0
     [4,] 20 0 0 0 0 0 0 0
     [5,] 19 0 0 0 0 0 0 0
     continA_B.8 continA_B.9 continA_B.10 continA_B.11 continA_B.12 continA_B.13 continA_B.14
     [1,] 0 0 0 0 0 0 0
     [2,] 0 0 0 0 0 0 0
     [3,] 0 0 0 0 0 0 1
     [4,] 0 0 0 0 0 0 0
     [5,] 0 0 0 0 0 0 0
     continA_B.15 continA_B.16 continA_B.17 continA_B.18 continA_B.19 continA_B.20 continA_B.21
     [1,] 0 0 0 0 0 0 0
     [2,] 0 0 0 0 0 0 0
     [3,] NA NA NA NA NA NA NA
     [4,] 0 0 0 0 0 1 NA
     [5,] 0 0 0 0 1 NA NA
     continA_B.22 continA_B.23 continA_B.24 continA_B.25 continA_B.26 continA_B.27 continA_B.28
     [1,] 0 0 1 NA NA NA NA
     [2,] 0 0 1 NA NA NA NA
     [3,] NA NA NA NA NA NA NA
     [4,] NA NA NA NA NA NA NA
     [5,] NA NA NA NA NA NA NA
     continA_B.29
     [1,] NA
     [2,] NA
     [3,] NA
     [4,] NA
     [5,] NA
     [1] "fitting the model: P(continA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.656607e+01 -1.172459e-11 -1.310221e-11 -2.568646e-11
     [1] "fitting the model: P(continA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.281376655 -0.035725822 0.006163052 0.051358250
     [1] "fitting the model: P(continA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.27317694 -0.10541349 -0.05938349 0.14004641
     [1] "fitting the model: P(continA_B.4|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.14507993 0.06777557 0.05215471 -0.09874913
     [1] "fitting the model: P(continA_B.5|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.24391898 0.26646186 0.19294229 0.06466046
     [1] "fitting the model: P(continA_B.6|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.11940473 0.27038874 -0.13810215 0.03946705
     [1] "fitting the model: P(continA_B.7|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.0604195588 0.1501921273 -0.0044245117 -0.0009702738
     [1] "fitting the model: P(continA_B.8|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.01782127 0.16553759 0.08395192 -0.02658259
     [1] "fitting the model: P(continA_B.9|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.957620941 0.071127732 0.032989031 -0.002554316
     [1] "fitting the model: P(continA_B.10|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.87405564 -0.14425677 -0.23472149 0.07557312
     [1] "fitting the model: P(continA_B.11|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.9199701 0.1352712 -0.1093724 0.1682282
     [1] "fitting the model: P(continA_B.12|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.82574393 -0.02757504 0.07179835 0.07635102
     [1] "fitting the model: P(continA_B.13|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.75744325 -0.17054856 0.08270185 0.09091752
     [1] "fitting the model: P(continA_B.14|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.7557954 0.2274203 0.1073792 0.1260005
     [1] "fitting the model: P(continA_B.15|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.4789349046 -0.1945962255 -0.0003716866 -0.1280978950
     [1] "fitting the model: P(continA_B.16|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.43274664 -0.10457586 0.05741394 -0.10350059
     [1] "fitting the model: P(continA_B.17|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.35536442 0.11120621 0.08692869 -0.14145183
     [1] "fitting the model: P(continA_B.18|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.38871979 -0.04875293 0.24156211 0.07361624
     [1] "fitting the model: P(continA_B.19|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.23116116 -0.06701096 -0.17561980 0.13424470
     [1] "fitting the model: P(continA_B.20|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.12407963 0.20765877 0.05094781 0.01987238
     [1] "fitting the model: P(continA_B.21|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.87127696 -0.05213833 -0.03626824 -0.12188588
     [1] "fitting the model: P(continA_B.22|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.715027286 -0.002665716 -0.224749173 -0.068448996
     [1] "fitting the model: P(continA_B.23|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.65153465 0.07484629 -0.07905875 0.09109542
     [1] "fitting the model: P(continA_B.24|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.39497072 0.06328347 0.06930376 -0.02412229
     [1] "fitting the model: P(continA_B.25|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.07288015 -0.01751414 0.16639030 -0.11292090
     [1] "fitting the model: P(continA_B.26|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -0.71680315 0.23239467 0.12029946 -0.04808753
     [1] "fitting the model: P(continA_B.27|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -0.18008178 0.15823414 0.04425133 0.28679861
     [1] "fitting the model: P(continA_B.28|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 7.012760e-09 -2.571018e-09 4.414688e-06
     [1] "fitting the model: P(continA_B.29|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for outcome continA succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for continuous outcome: continA"
     [1] "performing prediction for continuous outcome: continA"
     done successfully.
    
     ------------------- UNIT TEST SUMMARY ---------------------
    
     RUNIT TEST PROTOCOL -- Sun Apr 15 22:03:25 2018
     ***********************************************
     Number of test functions: 18
     Number of errors: 1
     Number of failures: 0
    
    
     1 Test Suite :
     stremr unit testing - 18 test functions, 1 error, 0 failures
     ERROR in test.speedglm.allestimators10Kdata: Error in make_report_rmd(OData, NPMSM = list(surv1, surv2), MSM = MSM.IPAW, :
     file '/tmp/RtmpYMYKLT/sim.data.example.fup.pdf' does not exist
     Error:
    
     unit testing failed (#test failures: 0, #R errors: 1)
    
     Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc

Version: 0.4
Check: tests
Result: ERROR
     Running ‘test-all.R’ [161s/339s]
    Running the tests in ‘tests/test-all.R’ failed.
    Last 13 lines of output:
     RUNIT TEST PROTOCOL -- Mon Mar 12 04:54:14 2018
     ***********************************************
     Number of test functions: 18
     Number of errors: 1
     Number of failures: 0
    
    
     1 Test Suite :
     stremr unit testing - 18 test functions, 1 error, 0 failures
     ERROR in test.speedglm.allestimators10Kdata: Error in readChar(con, 5L, useBytes = TRUE) : cannot open the connection
     Error:
    
     unit testing failed (#test failures: 0, #R errors: 1)
    
     Execution halted
Flavor: r-devel-osx-x86_64

Version: 0.4
Check: tests
Result: ERROR
     Running ‘test-all.R’ [134s/174s]
    Running the tests in ‘tests/test-all.R’ failed.
    Complete output:
     > ## unit tests will not be done if RUnit is not available
     > # setwd("..")
     > # getwd()
     > # library(RUnit)
     > if(require("RUnit", quietly=TRUE)) {
     + ## --- Setup ---
     +
     + pkg <- "stremr" # <-- Tested package name
     +
     + if(Sys.getenv("RCMDCHECK") == "FALSE") {
     + ## Path to unit tests for standalone running under Makefile (not R CMD check)
     + ## PKG/tests/../inst/unitTests
     + # path <- file.path(getwd(), "..", "inst", "unitTests")
     + } else {
     + ## Path to unit tests for R CMD check
     + ## PKG.Rcheck/tests/../PKG/unitTests
     + # path <- system.file(package=pkg, "RUnit")
     +
     + # REPLACED WITH:
     + path <- file.path(getwd(), "RUnit")
     + }
     +
     + cat("\nRunning unit tests\n")
     + print(list(pkg=pkg, getwd=getwd(), pathToUnitTests=path))
     +
     + library(package=pkg, character.only=TRUE)
     +
     + ## If desired, load the name space to allow testing of private functions
     + ## if (is.element(pkg, loadedNamespaces()))
     + ## attach(loadNamespace(pkg), name=paste("namespace", pkg, sep=":"), pos=3)
     + ##
     + ## or simply call PKG:::myPrivateFunction() in tests
     +
     + ## --- Testing ---
     +
     + ## Define tests
     + test.suite <- defineTestSuite(name=paste(pkg, "unit testing"),
     + # dirs="./RUnit",
     + dirs=path,
     + testFileRegexp = "^RUnit_tests_+",
     + testFuncRegexp = "^test.+",
     + rngKind = "Marsaglia-Multicarry",
     + rngNormalKind = "Kinderman-Ramage")
     + ## Run
     + tests <- runTestSuite(test.suite)
     +
     + ## Default report name
     + pathReport <- file.path(path, "report")
     +
     + ## Report to stdout and text files
     + cat("------------------- UNIT TEST SUMMARY ---------------------\n\n")
     + printTextProtocol(tests, showDetails=FALSE)
     + printTextProtocol(tests, showDetails=FALSE,
     + fileName=paste0(pathReport, "Summary.txt"))
     + printTextProtocol(tests, showDetails=TRUE,
     + fileName=paste0(pathReport, ".txt"))
     + ## Report to HTML file
     + printHTMLProtocol(tests, fileName=paste0(pathReport, ".html"))
     +
     + ## Return stop() to cause R CMD check stop in case of
     + ## - failures i.e. FALSE to unit tests or
     + ## - errors i.e. R errors
     + tmp <- getErrors(tests)
     + if(tmp$nFail > 0 | tmp$nErr > 0) {
     + stop(paste("\n\nunit testing failed (#test failures: ", tmp$nFail,
     + ", #R errors: ", tmp$nErr, ")\n\n", sep=""))
     + }
     + } else {
     + warning("cannot run unit tests -- package RUnit is not available")
     + }
    
     Running unit tests
     $pkg
     [1] "stremr"
    
     $getwd
     [1] "/home/hornik/tmp/R.check/r-patched-gcc/Work/PKGS/stremr.Rcheck/tests"
    
     $pathToUnitTests
     [1] "/home/hornik/tmp/R.check/r-patched-gcc/Work/PKGS/stremr.Rcheck/tests/RUnit"
    
    
    
     Executing test function test.GenericModelPredict ... Loading required package: data.table
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.6829138 1.4512950 -0.4353432 0.5852046
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "catA"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: catA"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA, catA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "CategorModel outcome: catA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA_B.1, catA_B.2, catA_B.3"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "CategorModel outcome: catA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA_B.1, catA_B.2, catA_B.3"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for outcome based on stratified model for outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: catA"
     [1] "freq counts by bin for categorical outcome: "
    
     1 2 3
     4637 4621 4731
     [1] "binned dataset: "
     sA catA_B.1 catA_B.2 catA_B.3
     [1,] 2 NA 1 NA
     [2,] 3 NA 1 NA
     [3,] 2 NA 1 NA
     [4,] 2 NA 1 NA
     [5,] 2 NA 1 NA
     [1] "fitting the model: P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     [1] "fitting the model: P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -9.762950e-08 2.155173e-06 NA
     [1] "fitting the model: P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for catA var succeeded...
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: catA"
     [1] "freq counts by bin for categorical outcome: "
    
     1 2 3
     4637 4621 4731
     [1] "binned dataset: "
     sA catA_B.1 catA_B.2 catA_B.3
     [1,] 2 NA 1 NA
     [2,] 3 NA 1 NA
     [3,] 2 NA 1 NA
     [4,] 2 NA 1 NA
     [5,] 2 NA 1 NA
     [1] "fitting the model: P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     [1] "fitting the model: P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -3.738646e-08 -2.346217e-07 -2.013073e-07
     [1] "fitting the model: P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for catA var succeeded...
     fit for catA var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: catA"
     [1] "performing prediction for categorical outcome: catA"
     [1] "performing prediction for categorical outcome: catA"
     [1] "performing prediction for outcome based on stratified model: catA"
     [1] "performing prediction for categorical outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing prediction for categorical outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     done successfully.
    
    
    
     Executing test function test.Nsamp.n.test ... done successfully.
    
    
    
     Executing test function test.options ... [1] "Possible `stremr` options:"
     [1] "fit.package" "fit.algorithm" "bin.method"
     [4] "nbins" "maxncats" "maxNperBin"
     [7] "lower_bound_zero_Q" "skip_update_zero_Q"
     Error in stremrOptions("blahblah") :
     blahblah: this options does not exist
     Error in stremrOptions("blahblah", 5) : Invalid option name: blahblah
     Error in if (!(fit.algorithm %in% allowed.fit.algorithm)) stop("fit.algorithm must be one of: " %+% :
     argument is of length zero
     Error in set_all_stremr_options(fit.package = "speedglm", fit.algorithm = "blahblah", :
     fit.algorithm must be one of: glm, gbm, randomForest, deeplearning
     Error in set_all_stremr_options(fit.package = "blahblah", fit.algorithm = "glm", :
     fit.package must be one of: speedglm, glm, h2o
     Error in set_all_stremr_options(fit.package = "speedglm", fit.algorithm = "glm", :
     bin.method must be one of: equal.mass, equal.len, dhist
     $fit.package
     [1] "speedglm"
    
     $fit.algorithm
     [1] "glm"
    
     $bin.method
     [1] "equal.mass"
    
     $nbins
     [1] 10
    
     $maxncats
     [1] 20
    
     $maxNperBin
     [1] 500
    
     $lower_bound_zero_Q
     [1] TRUE
    
     $skip_update_zero_Q
     [1] TRUE
    
     done successfully.
    
    
    
     Executing test function test.regressionCases ... done successfully.
    
    
    
     Executing test function test.t.error ... done successfully.
    
    
    
     Executing test function test.DataStorageClass ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     Error in OData$get.outvar(var = "blah") :
     requested variable blah does not exist in DataStorageClass!
     done successfully.
    
    
    
     Executing test function test.error.fits.stratify ... Error in create_subset_expr(outvars = res$outvars, stratify.EXPRS = stratify.EXPRS) :
     Could not locate the appropriate regression variable(s) within the supplied stratification list stratify_CENS, stratify_TRT or stratify_MONITOR.
     The regression outcome variable(s) specified in gform_CENS, gform_TRT or gform_MONITOR were: ( 'C,TI' )
     However, the item names in the matching stratification list were: ( 'wrongC,TI,N' )
     done successfully.
    
    
    
     Executing test function test.helperfuns ... done successfully.
    
    
    
     Executing test function test.model.fits.stratify ... done successfully.
    
    
    
     Executing test function test.model.fits.categorCENSOR ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.52652066 0.05456581 0.10858685
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.19067146 NA 0.43343872 -0.01789425
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01340964 NA NA -0.03245807 -0.01185101
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 8.599825e-13 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.29183433 -0.07998923 0.03081559
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.64534186 NA 0.09366241 -0.16923766
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01135495 NA NA -0.02269938 -0.01321850
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 1,t > 0 & C == 1)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 1"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 1"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 1 & TI == 1,t > 0 & C == 1 & TI == 1)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 1 & TI == 1"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 1 & TI == 1"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 8.599825e-13 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.29183433 -0.07998923 0.03081559
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     NA NA NA NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     NA 0.4924641 0.1270091 -0.1911502
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 1 & TI == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     NA NA NA NA NA
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 1 & TI == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     NA NA NA NA NA
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,t > 0L & TI.tminus1 == 0L,t > 0L & TI.tminus1 == 1L)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 1L"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.52652066 0.05456581 0.10858685
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.64534186 NA 0.09366241 -0.16923766
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     -0.01467019 -0.45533330 NA NA NA
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     -0.01135495 -0.02269938 -0.01321850 NA NA
     fit for N var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -21.2548627 0.9100488 2.1714524 19.1407169
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 1L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 1.092843e-07 1.158713e-07 1.320318e-07
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "performing prediction for outcome based on stratified model: TI"
     done successfully.
    
    
    
     Executing test function test.model.fits.categorCENSOR2 ... Loading required package: magrittr
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "CatC"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: CatC"
     [1] "StratifiedModel expressions: (t < 16,t == 16)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC, CatC"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     ...fitting a model for categorical censoring...
     [1] "CategorModel outcome: CatC"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC_B.1, CatC_B.2, CatC_B.3"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.1|highA1c);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.2|highA1c);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.3|highA1c);\\ Stratify: t < 16"
     ...fitting a model for categorical censoring...
     [1] "CategorModel outcome: CatC"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC_B.1, CatC_B.2, CatC_B.3"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.1|highA1c);\\ Stratify: t == 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.2|highA1c);\\ Stratify: t == 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.3|highA1c);\\ Stratify: t == 16"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,(t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L),(t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L),(t > 0L) & (barTIm1eq0 == 1L))"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI, TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L)"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L)"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (barTIm1eq0 == 1L)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: CatC"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: CatC"
     [1] "freq counts by bin for categorical outcome: "
    
     0 1 2
     7469 347 314
     [1] "binned dataset: "
     sA CatC_B.1 CatC_B.2 CatC_B.3
     [1,] 0 0 0 NA
     [2,] 0 0 0 NA
     [3,] 1 1 NA NA
     [4,] 0 0 0 NA
     [5,] 0 0 0 NA
     [1] "fitting the model: P(CatC_B.1|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -3.1487960 0.1616531
     [1] "fitting the model: P(CatC_B.2|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -3.13719779 -0.08098814
     [1] "fitting the model: P(CatC_B.3|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     NA NA
     fit for CatC var succeeded...
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: CatC"
     [1] "freq counts by bin for categorical outcome: "
    
     0 1 2
     7469 347 314
     [1] "binned dataset: "
     sA CatC_B.1 CatC_B.2 CatC_B.3
     [1,] 0 0 0 NA
     [2,] 0 0 0 NA
     [3,] 1 1 NA NA
     [4,] 0 0 0 NA
     [5,] 0 0 0 NA
     [1] "fitting the model: P(CatC_B.1|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -2.9593646 0.5614693
     [1] "fitting the model: P(CatC_B.2|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -4.89784 -15.66823
     [1] "fitting the model: P(CatC_B.3|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     NA NA
     fit for CatC var succeeded...
     fit for CatC var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.1141458 0.9100488 2.1714524 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.656607e+01 2.444839e-12 2.082888e-12 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -21.2548627 0.9100488 2.1714524 19.1407169
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: CatC"
     [1] "performing prediction for categorical outcome: CatC"
     [1] "performing prediction for categorical outcome: CatC"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "N"
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     done successfully.
    
    
    
     Executing test function test.buildingblocks ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     Error in getIPWeights(OData = OData, intervened_TRT = "TI.set1", rule_name = "TI1") :
     ...cannot locate propensity scores in 'OData' object - must run fitPropensity(...) prior to calling this function
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t < 16,t == 16)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 16"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t < 16"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.198768e-13 -5.125570e-14
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 16"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -6.143963e-14 -2.839781e-14
     fit for C var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "performing estimation for the following TRT/MONITOR rules found in column 'rule.name': TI0,TI1"
     [1] "periods"
     [1] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
     [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     [1] "Periods.0to0_TI0"
     [1] "Periods.1to1_TI0"
     [1] "Periods.2to2_TI0"
     [1] "Periods.3to3_TI0"
     [1] "Periods.4to4_TI0"
     [1] "Periods.5to5_TI0"
     [1] "Periods.6to6_TI0"
     [1] "Periods.7to7_TI0"
     [1] "Periods.8to11_TI0"
     [1] "Periods.12to15_TI0"
     [1] "Periods.0to0_TI1"
     [1] "Periods.1to1_TI1"
     [1] "Periods.2to2_TI1"
     [1] "Periods.3to3_TI1"
     [1] "Periods.4to4_TI1"
     [1] "Periods.5to5_TI1"
     [1] "Periods.6to6_TI1"
     [1] "Periods.7to7_TI1"
     [1] "Periods.8to11_TI1"
     [1] "Periods.12to15_TI1"
     ...fitting hazard MSM with speedglm::speedglm.wfit...
     [1] "MSM fits"
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     -5.465039e+00 -4.324378e+00 -4.012934e+00 -1.166619e+15
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     -6.871355e+14 -4.884654e+14 -6.732368e+00 -6.414551e+00
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     -2.490327e+15 -3.057464e+15 -3.089228e+00 -4.070768e+00
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     -4.097356e+00 -1.444049e+01 -3.626218e+00 -4.172158e+00
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     -5.928687e+00 -3.921940e+00 -4.645602e+00 -3.410729e+00
     ...evaluating MSM-based survival curves...
     ...evaluating SEs based on MSM hazard fit and the estimated IC...
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     9.379699e-17 2.900859e-16 7.383396e-15 7.293270e+00
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     6.561300e+01 4.445403e+02 3.220105e-14 2.800474e-14
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.030033e+02 7.899748e+02 7.913397e-18 2.865011e-18
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     7.009244e-18 4.879654e-08 1.399031e-19 7.292022e-18
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     2.532557e-18 1.471364e-17 3.615109e-16 1.717254e-15
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     9.340525e-15 3.126553e-15 1.800440e-14 3.336980e+14
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     7.563694e+14 1.183848e+15 5.560005e-15 5.426432e-15
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     1.830248e+14 5.408850e+14 4.968619e-15 3.569094e-15
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     6.622362e-15 1.000001e+00 8.253617e-17 2.682887e-15
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     3.708932e-15 2.085976e-15 9.255499e-15 3.032843e-15
     [1] "Should all be very small: "
     [1] 3.953818e-17 7.916801e-17 2.288376e-16 2.288376e-16 2.288376e-16
     [6] 2.288376e-16 2.227361e-16 2.339417e-16 2.339417e-16 2.339417e-16
     [11] 2.339417e-16 2.339417e-16 2.339417e-16 2.339417e-16 2.339417e-16
     [16] 2.339417e-16
     [1] "Should all be very small: "
     [1] 2.087237e-16 2.567391e-16 1.552191e-16 4.951408e-07 4.823035e-07
     [6] 4.749798e-07 4.737188e-07 4.645200e-07 4.601013e-07 4.557247e-07
     [11] 4.513896e-07 4.470959e-07 4.328058e-07 4.189726e-07 4.055814e-07
     [16] 3.926183e-07
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -2.240428e-13 -9.163027e-14
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "performing estimation for the following TRT/MONITOR rules found in column 'rule.name': TI0,TI1"
     [1] "periods"
     [1] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
     [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     [1] "Periods.0to0_TI0"
     [1] "Periods.1to1_TI0"
     [1] "Periods.2to2_TI0"
     [1] "Periods.3to3_TI0"
     [1] "Periods.4to4_TI0"
     [1] "Periods.5to5_TI0"
     [1] "Periods.6to6_TI0"
     [1] "Periods.7to7_TI0"
     [1] "Periods.8to11_TI0"
     [1] "Periods.12to15_TI0"
     [1] "Periods.0to0_TI1"
     [1] "Periods.1to1_TI1"
     [1] "Periods.2to2_TI1"
     [1] "Periods.3to3_TI1"
     [1] "Periods.4to4_TI1"
     [1] "Periods.5to5_TI1"
     [1] "Periods.6to6_TI1"
     [1] "Periods.7to7_TI1"
     [1] "Periods.8to11_TI1"
     [1] "Periods.12to15_TI1"
     ...fitting hazard MSM with speedglm::speedglm.wfit...
     [1] "MSM fits"
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     -5.479625e+00 -4.224521e+15 -4.040682e+15 -3.195295e+15
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     -3.082898e+15 -2.778817e+15 -3.052026e+15 -3.796228e+15
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     -2.715406e+15 -1.534193e+15 -3.048470e+00 -4.020852e+00
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     -4.106498e+00 -1.007712e+01 -3.450746e+00 -4.160778e+00
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     -5.909203e+00 -4.008647e+00 -4.781623e+00 -3.422484e+15
     ...evaluating MSM-based survival curves...
     ...evaluating SEs based on MSM hazard fit and the estimated IC...
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     1.363995e-15 3.892340e+00 1.153066e+02 3.014492e+03
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     2.096739e+04 2.100000e+04 1.300000e+04 5.000000e+03
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.700000e+04 1.000000e+04 2.218218e-17 1.992734e-17
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     1.087903e-17 1.670762e-05 2.380815e-17 8.984546e-17
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     4.050727e-18 8.676045e-17 3.446043e-04 2.159757e+02
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     2.012238e-14 5.581563e+13 7.715289e+13 2.180508e+14
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     2.367837e+14 2.874638e+14 2.419289e+14 1.178953e+14
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.980323e+14 4.949011e+14 9.314984e-15 1.161900e-14
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     3.404072e-15 1.000042e+00 9.042079e-16 3.580885e-15
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     4.712621e-16 6.766642e-16 1.571325e-04 1.801860e+14
     [1] "Should all be very small: "
     [1] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [6] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [11] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [16] 8.330934e-17
     [1] "Should all be very small: "
     [1] 3.999902e-16 2.024836e-16 2.525296e-16 3.877971e-05 3.758736e-05
     [6] 3.701017e-05 3.690999e-05 3.625173e-05 3.706763e-05 3.786745e-05
     [11] 3.865142e-05 3.941974e-05 3.941974e-05 3.941974e-05 3.941974e-05
     [16] 3.941974e-05
     Error in process_opt_wts(wts_data_used, weights, nodes) :
     input 'weights' must be a data.table with 3 columns, two of which must be named as: 'ID' and 't'.
     In addition: Warning messages:
     1: glm.fit: algorithm did not converge
     2: glm.fit: algorithm did not converge
     3: glm.fit: algorithm did not converge
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -5.8682574 0.2154351 3.3021509 0.4033691 NA 0.7501467 NA
     [1] "Surv est: 0.983758322675102"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=0: 0.01624"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -4.67474313 0.19724908 2.21184261 -0.09839186 0.76483183 0.36869687
     TI.tminus1
     -0.98759997
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.48082464 0.25283340 2.46508499 0.04786835 NA -0.43706261
     TI.tminus1
     NA
     [1] "Surv est: 0.969902221464484"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=1: 0.0301"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.8073588 -1.1071567 1.3574257 -0.4540453 0.6083749 0.3767599 -1.4726757
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7570081 -0.3346276 1.4801253 -0.3532999 0.5055449 -0.5127511 -0.6589153
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.90325161 -0.07708853 2.01607750 -0.02829320 NA -0.32644563
     TI.tminus1
     NA
     [1] "Surv est: 0.953782240282527"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=2: 0.04622"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.2729961 0.6045142 2.3185601 -1.4506484 0.4525435 -1.0902410 -1.7027505
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.45925760 -0.49121038 1.40054082 -0.35287095 0.50934192 -0.02283871
     TI.tminus1
     -1.28687470
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8442520 -0.1010111 1.5056775 -0.2372471 0.4546915 -0.4782690 -0.6244729
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.94053966 0.04857403 1.99765895 0.01058704 NA -0.32554792
     TI.tminus1
     NA
     [1] "Surv est: 0.953681572539541"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04632"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.0863662 1.4415952 1.1242617 -0.4941329 -0.1391926 -0.8298997 -0.6156850
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1883548 1.2010569 1.3144619 -0.3947993 0.1333006 -0.9913184 -0.5170650
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.11978976 0.36019767 1.14780785 -0.23837798 0.37263297 -0.05869163
     TI.tminus1
     -0.85675524
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.6602088 0.3624027 1.3288288 -0.1996436 0.3619692 -0.4185487 -0.4804042
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.757594710 0.346812991 1.758549008 0.002438552 NA -0.302239540
     TI.tminus1
     NA
     [1] "Surv est: 0.943575229684677"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.05642"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.694637 0.368584 3.290803 -0.666631 NA NA NA
     [1] "tmle update: -0.00149135496809919"
     [1] "Surv est: 0.984107401301778"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=0: 0.01589"
     [1] "...empirical mean of the estimated EIC: -3.09079900454493e-05"
     [1] "...estimated TMLE variance: 2.41999050417123e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8004930 0.9282348 0.6879804 -0.5514791 0.7438655 NA NA
     [1] "tmle update: 0.0727160966327068"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6000572 0.5722892 2.2618565 -0.7563574 NA NA NA
     [1] "tmle update: -0.0022357049164653"
     [1] "Surv est: 0.969834495012909"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=1: 0.03017"
     [1] "...empirical mean of the estimated EIC: -6.07101133764977e-05"
     [1] "...estimated TMLE variance: 6.61356670225727e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9817186 -17.2807447 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595614761723"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715771607933"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470300657529"
     [1] "Surv est: 0.951909613102674"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=2: 0.04809"
     [1] "...empirical mean of the estimated EIC: -0.00010436571628225"
     [1] "...estimated TMLE variance: 0.000251078927354862"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595625433471"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715771369513"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470300648418"
     [1] "Surv est: 0.95190961310293"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04809"
     [1] "...empirical mean of the estimated EIC: -0.000104365720571848"
     [1] "...estimated TMLE variance: 0.000251078927359577"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.209019147885717"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8958776 0.4984205 0.7750137 1.4400473 0.1142727 NA NA
     [1] "tmle update: 0.0520880449204392"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1879874 -0.3427790 0.1064457 -0.4879009 0.5164562 NA NA
     [1] "tmle update: -0.00448980897354264"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7827815 0.1202478 0.3514419 -0.6841186 0.4586810 NA NA
     [1] "tmle update: 0.0158905661689546"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.4482301 0.1976754 1.4967452 -0.5174974 NA NA NA
     [1] "tmle update: -0.00227377143477276"
     [1] "Surv est: 0.925542187707399"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.07446"
     [1] "...empirical mean of the estimated EIC: -0.000520790968265705"
     [1] "...estimated TMLE variance: 0.00803708770988044"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.0048959544125669"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715758304584"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470301977723"
     [1] "Surv est: 0.951909613112289"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04809"
     [1] "...empirical mean of the estimated EIC: -1.65538533979754e-05"
     [1] "...estimated TMLE variance: 8.3806787779791e-06"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.209019147869959"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8958776 0.4984205 0.7750137 1.4400473 0.1142727 NA NA
     [1] "tmle update: 0.0520880449202836"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1879874 -0.3427790 0.1064457 -0.4879009 0.5164562 NA NA
     [1] "tmle update: -0.00448980955099783"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7827815 0.1202478 0.3514419 -0.6841186 0.4586810 NA NA
     [1] "tmle update: 0.0158905661764066"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.4482301 0.1976754 1.4967452 -0.5174974 NA NA NA
     [1] "tmle update: -0.00227377139578826"
     [1] "Surv est: 0.925542187729508"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.07446"
     [1] "...empirical mean of the estimated EIC: -8.12433860103523e-05"
     [1] "...estimated TMLE variance: 0.00019629047768188"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: 0.00455038396959821"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5351943 -0.2698513 0.0819634 -1.1897532 1.1194722 NA NA
     [1] "tmle update: 0.00148791277372786"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.9037005 0.1316045 1.9048099 -0.7888752 NA NA NA
     [1] "tmle update: 0.0038737545211174"
     [1] "Surv est: 0.952423126954576"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04758"
     [1] "...empirical mean of the estimated EIC: -3.11352727229658e-05"
     [1] "...estimated TMLE variance: 4.05438882728483e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.0043556607594549"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -5.1065413 0.4996280 0.7537557 1.4595663 0.1268353 NA NA
     [1] "tmle update: -6.23198919478809e-11"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.365723662 -0.465839994 0.005840225 -0.509288785 0.596038204 NA
     TI.tminus1
     NA
     [1] "tmle update: -4.44506521637441e-10"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.88176714 0.08310961 0.32781298 -0.75064933 0.51647978 NA
     TI.tminus1
     NA
     [1] "tmle update: 5.99566016142493e-11"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.5397115 0.1898817 1.5664979 -0.5505100 NA NA NA
     [1] "tmle update: 0.0027933549293886"
     [1] "Surv est: 0.931389922902869"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.06861"
     [1] "...empirical mean of the estimated EIC: -3.04000131367507e-05"
     [1] "...estimated TMLE variance: 5.41527268962014e-05"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -2.240428e-13 -9.163027e-14
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -4.661343e-14 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.830025e-13 -7.964050e-14
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     1.2490429 NA -0.4673254 -0.1775312
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.03015004 NA NA 0.01124218 -0.01120127
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -4.661343e-14 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.830025e-13 -7.964050e-14
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     1.2490429 NA -0.4673254 -0.1775312
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.03015004 NA NA 0.01124218 -0.01120127
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     done successfully.
    
    
    
     Executing test function test.speedglm.allestimators10Kdata ... [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     writing report to directory: /tmp/RtmpJNwZge
     writing related figures to report subdirectory: figure.sim.data.example.fup2
    
    
     processing file: /tmp/RtmpJNwZge/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
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     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
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     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
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     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
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     ordinary text without R code
    
     output file: /tmp/RtmpJNwZge/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmpJNwZge/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpJNwZge/sim.data.example.fup2.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-patched-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpJNwZge/rmarkdown-str5ea350aa2a39.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup2.html
     writing report to directory: /tmp/RtmpJNwZge
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpJNwZge/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
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     label: unnamed-chunk-1 (with options)
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     output file: /tmp/RtmpJNwZge/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmpJNwZge/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpJNwZge/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-patched-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpJNwZge/rmarkdown-str5ea3644c5773.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpJNwZge
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpJNwZge/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
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     output file: /tmp/RtmpJNwZge/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmpJNwZge/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpJNwZge/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-patched-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpJNwZge/rmarkdown-str5ea3147489cf.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpJNwZge
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpJNwZge/report-script-rmd.spin.Rmd
     inline R code fragments
    
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     output file: /tmp/RtmpJNwZge/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmpJNwZge/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpJNwZge/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-patched-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpJNwZge/rmarkdown-str5ea3550b852c.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpJNwZge
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpJNwZge/report-script-rmd.spin.Rmd
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     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
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     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
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     $ echo : logi FALSE
     $ fig.width : num 5
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     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
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     $ echo : logi FALSE
     $ results: chr "asis"
    
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     output file: /tmp/RtmpJNwZge/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmpJNwZge/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpJNwZge/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-patched-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpJNwZge/rmarkdown-str5ea359a8faba.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpJNwZge
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpJNwZge/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
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     output file: /tmp/RtmpJNwZge/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmpJNwZge/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpJNwZge/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-patched-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpJNwZge/rmarkdown-str5ea32eb83f21.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmpJNwZge
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmpJNwZge/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
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     inline R code fragments
    
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     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
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     inline R code fragments
    
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     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
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     output file: /tmp/RtmpJNwZge/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmpJNwZge/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpJNwZge/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-patched-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmpJNwZge/rmarkdown-str5ea37a7dd342.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
    
    
     processing file: /tmp/RtmpJNwZge/report-script-rmd.spin.Rmd
     inline R code fragments
    
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     $ fig.width : num 5
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     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     !!! Error: Cannot write tmp file `tmp-pdfcrop-23653.tex' (Read-only file system)!
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     inline R code fragments
    
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     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     !!! Error: Cannot write tmp file `tmp-pdfcrop-23963.tex' (Read-only file system)!
     inline R code fragments
    
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     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     !!! Error: Cannot write tmp file `tmp-pdfcrop-24116.tex' (Read-only file system)!
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     output file: /tmp/RtmpJNwZge/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmpJNwZge/report-script-rmd.utf8.md --to latex --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmpJNwZge/sim.data.example.fup.tex --table-of-contents --toc-depth 2 --template /home/hornik/tmp/R.check/r-patched-gcc/Work/build/Packages/rmarkdown/rmd/latex/default-1.17.0.2.tex --number-sections --highlight-style tango --latex-engine pdflatex --variable graphics=yes --variable 'geometry:margin=1in'
     You are recommended to install the tinytex package to build PDF.FALSE
     Latexmk: This is Latexmk, John Collins, 1 January 2015, version: 4.41.
     Cannot write file 'sim.data.example.fup.aux'
    
     Latexmk, John Collins, 1 January 2015. Version 4.41
     Timing stopped at: 38.94 2.092 55.21
     Error in make_report_rmd(OData, NPMSM = list(surv1, surv2), MSM = MSM.IPAW, :
     Failed to compile /tmp/RtmpJNwZge/sim.data.example.fup.tex.
     done successfully.
    
    
    
     Executing test function test.speedglm.stochastic.TMLE.NDE.1Kdata ... done successfully.
    
    
    
     Executing test function test.GCOMP.TMLE.10Kdata ... done successfully.
    
    
    
     Executing test function test.directRegressionDefn.10Kdata ... done successfully.
    
    
    
     Executing test function test.iterTMLE.10Kdata ... done successfully.
    
    
    
     Executing test function test.ContinModel ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "continA"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: continA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "ContinModel outcome: continA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: continA_B.1, continA_B.2, continA_B.3, continA_B.4, continA_B.5, continA_B.6, continA_B.7, continA_B.8, continA_B.9, continA_B.10, continA_B.11, continA_B.12, continA_B.13, continA_B.14, continA_B.15, continA_B.16, continA_B.17, continA_B.18, continA_B.19, continA_B.20, continA_B.21, continA_B.22, continA_B.23, continA_B.24, continA_B.25, continA_B.26, continA_B.27, continA_B.28, continA_B.29"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 29"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.4|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.5|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.6|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.7|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.8|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.9|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.10|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.11|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.12|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.13|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.14|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.15|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.16|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.17|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.18|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.19|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.20|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.21|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.22|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.23|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.24|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.25|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.26|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.27|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.28|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.29|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for continuous outcome: continA"
     [1] "freq counts by bin for continuous outcome: "
    
     2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
     519 518 518 518 518 518 518 518 518 518 518 518 518 519 518 518 518 518 518 518 518 518 518 518 518
     27 28
     518 519
     [1] "binned dataset: "
     continA_B.1 continA_B.2 continA_B.3 continA_B.4 continA_B.5 continA_B.6 continA_B.7
     [1,] 5 0 0 0 0 1 NA NA
     [2,] 24 0 0 0 0 0 0 0
     [3,] 27 0 0 0 0 0 0 0
     [4,] 26 0 0 0 0 0 0 0
     [5,] 21 0 0 0 0 0 0 0
     continA_B.8 continA_B.9 continA_B.10 continA_B.11 continA_B.12 continA_B.13 continA_B.14
     [1,] NA NA NA NA NA NA NA
     [2,] 0 0 0 0 0 0 0
     [3,] 0 0 0 0 0 0 0
     [4,] 0 0 0 0 0 0 0
     [5,] 0 0 0 0 0 0 0
     continA_B.15 continA_B.16 continA_B.17 continA_B.18 continA_B.19 continA_B.20 continA_B.21
     [1,] NA NA NA NA NA NA NA
     [2,] 0 0 0 0 0 0 0
     [3,] 0 0 0 0 0 0 0
     [4,] 0 0 0 0 0 0 0
     [5,] 0 0 0 0 0 0 1
     continA_B.22 continA_B.23 continA_B.24 continA_B.25 continA_B.26 continA_B.27 continA_B.28
     [1,] NA NA NA NA NA NA NA
     [2,] 0 0 1 NA NA NA NA
     [3,] 0 0 0 0 0 1 NA
     [4,] 0 0 0 0 1 NA NA
     [5,] NA NA NA NA NA NA NA
     continA_B.29
     [1,] NA
     [2,] NA
     [3,] NA
     [4,] NA
     [5,] NA
     [1] "fitting the model: P(continA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.656607e+01 -1.172459e-11 -1.310221e-11 -2.568646e-11
     [1] "fitting the model: P(continA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.31787630 0.07625915 -0.10603931 0.13353991
     [1] "fitting the model: P(continA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.24469974 0.01488067 0.04477374 0.02794799
     [1] "fitting the model: P(continA_B.4|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.14806299 -0.10857927 -0.16752625 0.02376434
     [1] "fitting the model: P(continA_B.5|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.11929428 0.23537467 -0.00784874 -0.08265993
     [1] "fitting the model: P(continA_B.6|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.03550570 -0.23236472 -0.04578229 -0.04502934
     [1] "fitting the model: P(continA_B.7|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.00160656 -0.07787821 -0.02778741 -0.05572677
     [1] "fitting the model: P(continA_B.8|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.954882235 -0.400340625 0.007601606 -0.009884802
     [1] "fitting the model: P(continA_B.9|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.903467215 -0.110331767 -0.177850282 0.007801704
     [1] "fitting the model: P(continA_B.10|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.89323514 0.08720076 0.03427924 -0.02716757
     [1] "fitting the model: P(continA_B.11|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.862608738 0.002879611 -0.073105653 0.079705856
     [1] "fitting the model: P(continA_B.12|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.80035091 -0.07589903 -0.00335757 0.06738577
     [1] "fitting the model: P(continA_B.13|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.725138955 0.254204643 0.005122964 -0.029254096
     [1] "fitting the model: P(continA_B.14|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.78062595 -0.08221742 0.05804806 0.24708997
     [1] "fitting the model: P(continA_B.15|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.607564411 0.128714498 0.123213088 0.006962749
     [1] "fitting the model: P(continA_B.16|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.48792031 0.14199352 -0.08290687 0.00478567
     [1] "fitting the model: P(continA_B.17|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.36099181 -0.12879984 0.10339216 -0.08762459
     [1] "fitting the model: P(continA_B.18|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.2831700 -0.1906067 0.1115763 -0.0446958
     [1] "fitting the model: P(continA_B.19|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.12990862 -0.09000253 -0.16849063 -0.04973316
     [1] "fitting the model: P(continA_B.20|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.02871357 -0.02011987 -0.02770807 -0.08250887
     [1] "fitting the model: P(continA_B.21|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.93931143 0.15340079 -0.21252129 0.02787789
     [1] "fitting the model: P(continA_B.22|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.73110948 -0.07972099 -0.19571327 -0.02708792
     [1] "fitting the model: P(continA_B.23|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.5696762 -0.2434877 -0.1342253 0.0227689
     [1] "fitting the model: P(continA_B.24|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.386037369 -0.052086075 0.006858624 0.006861756
     [1] "fitting the model: P(continA_B.25|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.09288633 -0.31018330 0.05784782 0.02687063
     [1] "fitting the model: P(continA_B.26|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -0.7287933 -0.1080867 -0.1613833 0.1505283
     [1] "fitting the model: P(continA_B.27|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.1277048 -0.1335444 -0.1590182 -0.1506478
     [1] "fitting the model: P(continA_B.28|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -5.676866e-07 2.712346e-08 -6.691864e-08
     [1] "fitting the model: P(continA_B.29|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for outcome continA succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for continuous outcome: continA"
     [1] "performing prediction for continuous outcome: continA"
     done successfully.
    
     ------------------- UNIT TEST SUMMARY ---------------------
    
     RUNIT TEST PROTOCOL -- Mon Apr 16 10:31:13 2018
     ***********************************************
     Number of test functions: 18
     Number of errors: 1
     Number of failures: 0
    
    
     1 Test Suite :
     stremr unit testing - 18 test functions, 1 error, 0 failures
     ERROR in test.speedglm.allestimators10Kdata: Error in make_report_rmd(OData, NPMSM = list(surv1, surv2), MSM = MSM.IPAW, :
     Failed to compile /tmp/RtmpJNwZge/sim.data.example.fup.tex.
     Error:
    
     unit testing failed (#test failures: 0, #R errors: 1)
    
     Execution halted
Flavor: r-patched-linux-x86_64

Version: 0.4
Check: tests
Result: ERROR
     Running ‘test-all.R’ [237s/267s]
    Running the tests in ‘tests/test-all.R’ failed.
    Complete output:
     > ## unit tests will not be done if RUnit is not available
     > # setwd("..")
     > # getwd()
     > # library(RUnit)
     > if(require("RUnit", quietly=TRUE)) {
     + ## --- Setup ---
     +
     + pkg <- "stremr" # <-- Tested package name
     +
     + if(Sys.getenv("RCMDCHECK") == "FALSE") {
     + ## Path to unit tests for standalone running under Makefile (not R CMD check)
     + ## PKG/tests/../inst/unitTests
     + # path <- file.path(getwd(), "..", "inst", "unitTests")
     + } else {
     + ## Path to unit tests for R CMD check
     + ## PKG.Rcheck/tests/../PKG/unitTests
     + # path <- system.file(package=pkg, "RUnit")
     +
     + # REPLACED WITH:
     + path <- file.path(getwd(), "RUnit")
     + }
     +
     + cat("\nRunning unit tests\n")
     + print(list(pkg=pkg, getwd=getwd(), pathToUnitTests=path))
     +
     + library(package=pkg, character.only=TRUE)
     +
     + ## If desired, load the name space to allow testing of private functions
     + ## if (is.element(pkg, loadedNamespaces()))
     + ## attach(loadNamespace(pkg), name=paste("namespace", pkg, sep=":"), pos=3)
     + ##
     + ## or simply call PKG:::myPrivateFunction() in tests
     +
     + ## --- Testing ---
     +
     + ## Define tests
     + test.suite <- defineTestSuite(name=paste(pkg, "unit testing"),
     + # dirs="./RUnit",
     + dirs=path,
     + testFileRegexp = "^RUnit_tests_+",
     + testFuncRegexp = "^test.+",
     + rngKind = "Marsaglia-Multicarry",
     + rngNormalKind = "Kinderman-Ramage")
     + ## Run
     + tests <- runTestSuite(test.suite)
     +
     + ## Default report name
     + pathReport <- file.path(path, "report")
     +
     + ## Report to stdout and text files
     + cat("------------------- UNIT TEST SUMMARY ---------------------\n\n")
     + printTextProtocol(tests, showDetails=FALSE)
     + printTextProtocol(tests, showDetails=FALSE,
     + fileName=paste0(pathReport, "Summary.txt"))
     + printTextProtocol(tests, showDetails=TRUE,
     + fileName=paste0(pathReport, ".txt"))
     + ## Report to HTML file
     + printHTMLProtocol(tests, fileName=paste0(pathReport, ".html"))
     +
     + ## Return stop() to cause R CMD check stop in case of
     + ## - failures i.e. FALSE to unit tests or
     + ## - errors i.e. R errors
     + tmp <- getErrors(tests)
     + if(tmp$nFail > 0 | tmp$nErr > 0) {
     + stop(paste("\n\nunit testing failed (#test failures: ", tmp$nFail,
     + ", #R errors: ", tmp$nErr, ")\n\n", sep=""))
     + }
     + } else {
     + warning("cannot run unit tests -- package RUnit is not available")
     + }
    
     Running unit tests
     $pkg
     [1] "stremr"
    
     $getwd
     [1] "/home/ripley/R/packages/tests32/stremr.Rcheck/tests"
    
     $pathToUnitTests
     [1] "/home/ripley/R/packages/tests32/stremr.Rcheck/tests/RUnit"
    
    
    
     Executing test function test.GenericModelPredict ... Loading required package: data.table
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.6829138 1.4512950 -0.4353432 0.5852046
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "catA"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: catA"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA, catA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "CategorModel outcome: catA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA_B.1, catA_B.2, catA_B.3"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "CategorModel outcome: catA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA_B.1, catA_B.2, catA_B.3"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for outcome based on stratified model for outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: catA"
     [1] "freq counts by bin for categorical outcome: "
    
     1 2 3
     4674 4625 4690
     [1] "binned dataset: "
     sA catA_B.1 catA_B.2 catA_B.3
     [1,] 1 NA 1 NA
     [2,] 2 NA 1 NA
     [3,] 2 NA 1 NA
     [4,] 1 NA 1 NA
     [5,] 2 NA 1 NA
     [1] "fitting the model: P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     [1] "fitting the model: P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -9.762950e-08 2.155173e-06 NA
     [1] "fitting the model: P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for catA var succeeded...
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: catA"
     [1] "freq counts by bin for categorical outcome: "
    
     1 2 3
     4674 4625 4690
     [1] "binned dataset: "
     sA catA_B.1 catA_B.2 catA_B.3
     [1,] 1 NA 1 NA
     [2,] 2 NA 1 NA
     [3,] 2 NA 1 NA
     [4,] 1 NA 1 NA
     [5,] 2 NA 1 NA
     [1] "fitting the model: P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     [1] "fitting the model: P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -3.738646e-08 -2.346217e-07 -2.013073e-07
     [1] "fitting the model: P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for catA var succeeded...
     fit for catA var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: catA"
     [1] "performing prediction for categorical outcome: catA"
     [1] "performing prediction for categorical outcome: catA"
     [1] "performing prediction for outcome based on stratified model: catA"
     [1] "performing prediction for categorical outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing prediction for categorical outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     done successfully.
    
    
    
     Executing test function test.Nsamp.n.test ... done successfully.
    
    
    
     Executing test function test.options ... [1] "Possible `stremr` options:"
     [1] "fit.package" "fit.algorithm" "bin.method"
     [4] "nbins" "maxncats" "maxNperBin"
     [7] "lower_bound_zero_Q" "skip_update_zero_Q"
     Error in stremrOptions("blahblah") :
     blahblah: this options does not exist
     Error in stremrOptions("blahblah", 5) : Invalid option name: blahblah
     Error in if (!(fit.algorithm %in% allowed.fit.algorithm)) stop("fit.algorithm must be one of: " %+% :
     argument is of length zero
     Error in set_all_stremr_options(fit.package = "speedglm", fit.algorithm = "blahblah", :
     fit.algorithm must be one of: glm, gbm, randomForest, deeplearning
     Error in set_all_stremr_options(fit.package = "blahblah", fit.algorithm = "glm", :
     fit.package must be one of: speedglm, glm, h2o
     Error in set_all_stremr_options(fit.package = "speedglm", fit.algorithm = "glm", :
     bin.method must be one of: equal.mass, equal.len, dhist
     $fit.package
     [1] "speedglm"
    
     $fit.algorithm
     [1] "glm"
    
     $bin.method
     [1] "equal.mass"
    
     $nbins
     [1] 10
    
     $maxncats
     [1] 20
    
     $maxNperBin
     [1] 500
    
     $lower_bound_zero_Q
     [1] TRUE
    
     $skip_update_zero_Q
     [1] TRUE
    
     done successfully.
    
    
    
     Executing test function test.regressionCases ... done successfully.
    
    
    
     Executing test function test.t.error ... done successfully.
    
    
    
     Executing test function test.DataStorageClass ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     Error in OData$get.outvar(var = "blah") :
     requested variable blah does not exist in DataStorageClass!
     done successfully.
    
    
    
     Executing test function test.error.fits.stratify ... Error in create_subset_expr(outvars = res$outvars, stratify.EXPRS = stratify.EXPRS) :
     Could not locate the appropriate regression variable(s) within the supplied stratification list stratify_CENS, stratify_TRT or stratify_MONITOR.
     The regression outcome variable(s) specified in gform_CENS, gform_TRT or gform_MONITOR were: ( 'C,TI' )
     However, the item names in the matching stratification list were: ( 'wrongC,TI,N' )
     done successfully.
    
    
    
     Executing test function test.helperfuns ... done successfully.
    
    
    
     Executing test function test.model.fits.stratify ... done successfully.
    
    
    
     Executing test function test.model.fits.categorCENSOR ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.52652066 0.05456581 0.10858685
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.19067146 NA 0.43343872 -0.01789425
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01340964 NA NA -0.03245807 -0.01185101
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 8.599825e-13 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.29183433 -0.07998923 0.03081559
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.64534186 NA 0.09366241 -0.16923766
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01135495 NA NA -0.02269938 -0.01321850
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 1,t > 0 & C == 1)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 1"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 1"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 1 & TI == 1,t > 0 & C == 1 & TI == 1)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 1 & TI == 1"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 1 & TI == 1"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 8.599825e-13 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.29183433 -0.07998923 0.03081559
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     NA NA NA NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     NA 0.4924641 0.1270091 -0.1911502
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 1 & TI == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     NA NA NA NA NA
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 1 & TI == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     NA NA NA NA NA
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,t > 0L & TI.tminus1 == 0L,t > 0L & TI.tminus1 == 1L)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 1L"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.52652066 0.05456581 0.10858685
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.64534186 NA 0.09366241 -0.16923766
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     -0.01467019 -0.45533330 NA NA NA
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     -0.01135495 -0.02269938 -0.01321850 NA NA
     fit for N var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -21.2548627 0.9100488 2.1714524 19.1407169
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 1L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 1.092843e-07 1.158713e-07 1.320318e-07
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "performing prediction for outcome based on stratified model: TI"
     done successfully.
    
    
    
     Executing test function test.model.fits.categorCENSOR2 ... Loading required package: magrittr
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "CatC"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: CatC"
     [1] "StratifiedModel expressions: (t < 16,t == 16)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC, CatC"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     ...fitting a model for categorical censoring...
     [1] "CategorModel outcome: CatC"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC_B.1, CatC_B.2, CatC_B.3"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.1|highA1c);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.2|highA1c);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.3|highA1c);\\ Stratify: t < 16"
     ...fitting a model for categorical censoring...
     [1] "CategorModel outcome: CatC"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC_B.1, CatC_B.2, CatC_B.3"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.1|highA1c);\\ Stratify: t == 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.2|highA1c);\\ Stratify: t == 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.3|highA1c);\\ Stratify: t == 16"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,(t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L),(t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L),(t > 0L) & (barTIm1eq0 == 1L))"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI, TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L)"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L)"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (barTIm1eq0 == 1L)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: CatC"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: CatC"
     [1] "freq counts by bin for categorical outcome: "
    
     0 1 2
     7469 347 314
     [1] "binned dataset: "
     sA CatC_B.1 CatC_B.2 CatC_B.3
     [1,] 0 0 0 NA
     [2,] 0 0 0 NA
     [3,] 1 1 NA NA
     [4,] 0 0 0 NA
     [5,] 0 0 0 NA
     [1] "fitting the model: P(CatC_B.1|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -3.1487960 0.1616531
     [1] "fitting the model: P(CatC_B.2|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -3.13719779 -0.08098814
     [1] "fitting the model: P(CatC_B.3|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     NA NA
     fit for CatC var succeeded...
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: CatC"
     [1] "freq counts by bin for categorical outcome: "
    
     0 1 2
     7469 347 314
     [1] "binned dataset: "
     sA CatC_B.1 CatC_B.2 CatC_B.3
     [1,] 0 0 0 NA
     [2,] 0 0 0 NA
     [3,] 1 1 NA NA
     [4,] 0 0 0 NA
     [5,] 0 0 0 NA
     [1] "fitting the model: P(CatC_B.1|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -2.9593646 0.5614693
     [1] "fitting the model: P(CatC_B.2|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -4.89784 -15.66823
     [1] "fitting the model: P(CatC_B.3|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     NA NA
     fit for CatC var succeeded...
     fit for CatC var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.1141458 0.9100488 2.1714524 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.656607e+01 2.444839e-12 2.082888e-12 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -21.2548627 0.9100488 2.1714524 19.1407169
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: CatC"
     [1] "performing prediction for categorical outcome: CatC"
     [1] "performing prediction for categorical outcome: CatC"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "N"
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     done successfully.
    
    
    
     Executing test function test.buildingblocks ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     Error in getIPWeights(OData = OData, intervened_TRT = "TI.set1", rule_name = "TI1") :
     ...cannot locate propensity scores in 'OData' object - must run fitPropensity(...) prior to calling this function
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t < 16,t == 16)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 16"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t < 16"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.198768e-13 -5.125570e-14
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 16"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -6.143963e-14 -2.839781e-14
     fit for C var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "performing estimation for the following TRT/MONITOR rules found in column 'rule.name': TI0,TI1"
     [1] "periods"
     [1] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
     [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     [1] "Periods.0to0_TI0"
     [1] "Periods.1to1_TI0"
     [1] "Periods.2to2_TI0"
     [1] "Periods.3to3_TI0"
     [1] "Periods.4to4_TI0"
     [1] "Periods.5to5_TI0"
     [1] "Periods.6to6_TI0"
     [1] "Periods.7to7_TI0"
     [1] "Periods.8to11_TI0"
     [1] "Periods.12to15_TI0"
     [1] "Periods.0to0_TI1"
     [1] "Periods.1to1_TI1"
     [1] "Periods.2to2_TI1"
     [1] "Periods.3to3_TI1"
     [1] "Periods.4to4_TI1"
     [1] "Periods.5to5_TI1"
     [1] "Periods.6to6_TI1"
     [1] "Periods.7to7_TI1"
     [1] "Periods.8to11_TI1"
     [1] "Periods.12to15_TI1"
     ...fitting hazard MSM with speedglm::speedglm.wfit...
     [1] "MSM fits"
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     -5.465039e+00 -4.324378e+00 -4.012934e+00 -1.166619e+15
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     -6.871355e+14 -4.884654e+14 -6.732368e+00 -6.414551e+00
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     -2.490327e+15 -3.057464e+15 -3.089228e+00 -4.070768e+00
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     -4.097356e+00 -1.444049e+01 -3.626218e+00 -4.172158e+00
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     -5.928687e+00 -3.921940e+00 -4.645602e+00 -3.410729e+00
     ...evaluating MSM-based survival curves...
     ...evaluating SEs based on MSM hazard fit and the estimated IC...
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     9.462573e-17 2.944089e-16 2.828261e-15 7.293270e+00
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     6.561300e+01 4.445403e+02 2.942740e-14 3.696352e-14
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.030033e+02 7.899748e+02 8.616021e-19 3.997853e-18
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     7.040425e-18 4.879654e-08 1.004232e-17 7.554828e-18
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     1.455016e-18 1.499928e-17 3.341834e-16 9.527988e-16
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     9.421742e-15 3.237747e-15 6.931219e-15 3.336980e+14
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     7.563694e+14 1.183848e+15 5.042360e-15 7.041551e-15
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     1.830248e+14 5.408850e+14 4.887755e-16 5.013825e-15
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     6.663849e-15 1.000001e+00 3.001987e-15 2.794958e-15
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     2.080482e-15 2.142088e-15 8.589764e-15 1.696652e-15
     [1] "Should all be very small: "
     [1] 3.995817e-17 2.563398e-18 1.217398e-16 1.217398e-16 1.217398e-16
     [6] 1.217398e-16 1.130589e-16 1.270720e-16 1.270720e-16 1.270720e-16
     [11] 1.270720e-16 1.270720e-16 1.270720e-16 1.270720e-16 1.270720e-16
     [16] 1.270720e-16
     [1] "Should all be very small: "
     [1] 1.939833e-17 6.272759e-17 1.621637e-16 4.951408e-07 4.823035e-07
     [6] 4.749798e-07 4.737188e-07 4.645200e-07 4.601013e-07 4.557247e-07
     [11] 4.513896e-07 4.470959e-07 4.328058e-07 4.189726e-07 4.055814e-07
     [16] 3.926183e-07
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -2.240428e-13 -9.163027e-14
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "performing estimation for the following TRT/MONITOR rules found in column 'rule.name': TI0,TI1"
     [1] "periods"
     [1] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
     [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     [1] "Periods.0to0_TI0"
     [1] "Periods.1to1_TI0"
     [1] "Periods.2to2_TI0"
     [1] "Periods.3to3_TI0"
     [1] "Periods.4to4_TI0"
     [1] "Periods.5to5_TI0"
     [1] "Periods.6to6_TI0"
     [1] "Periods.7to7_TI0"
     [1] "Periods.8to11_TI0"
     [1] "Periods.12to15_TI0"
     [1] "Periods.0to0_TI1"
     [1] "Periods.1to1_TI1"
     [1] "Periods.2to2_TI1"
     [1] "Periods.3to3_TI1"
     [1] "Periods.4to4_TI1"
     [1] "Periods.5to5_TI1"
     [1] "Periods.6to6_TI1"
     [1] "Periods.7to7_TI1"
     [1] "Periods.8to11_TI1"
     [1] "Periods.12to15_TI1"
     ...fitting hazard MSM with speedglm::speedglm.wfit...
     [1] "MSM fits"
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     -5.479625e+00 -4.224521e+15 -4.040682e+15 -3.195295e+15
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     -3.082898e+15 -2.778817e+15 -3.052026e+15 -3.796228e+15
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     -2.715406e+15 -1.534193e+15 -3.048470e+00 -4.020852e+00
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     -4.106498e+00 -1.007712e+01 -3.450746e+00 -4.160778e+00
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     -5.909203e+00 -4.008647e+00 -4.781623e+00 -3.422484e+15
     ...evaluating MSM-based survival curves...
     ...evaluating SEs based on MSM hazard fit and the estimated IC...
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     1.372220e-15 3.892340e+00 1.153066e+02 3.014492e+03
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     2.096739e+04 2.100000e+04 1.300000e+04 5.000000e+03
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.700000e+04 1.000000e+04 2.216689e-17 1.053539e-17
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     2.234741e-17 1.670762e-05 2.646152e-17 1.029625e-16
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     5.181238e-18 1.142027e-16 3.446043e-04 2.159757e+02
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     2.028144e-14 5.581563e+13 7.715289e+13 2.180508e+14
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     2.367837e+14 2.874638e+14 2.419289e+14 1.178953e+14
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.980323e+14 4.949011e+14 9.307628e-15 6.147405e-15
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     7.082937e-15 1.000042e+00 1.067397e-15 4.119857e-15
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     5.948334e-16 8.761861e-16 1.571325e-04 1.801860e+14
     [1] "Should all be very small: "
     [1] 8.388493e-17 8.388493e-17 8.388493e-17 8.388493e-17 8.388493e-17
     [6] 8.388493e-17 8.388493e-17 8.388493e-17 8.388493e-17 8.388493e-17
     [11] 8.388493e-17 8.388493e-17 8.388493e-17 8.388493e-17 8.388493e-17
     [16] 8.388493e-17
     [1] "Should all be very small: "
     [1] 3.995437e-16 2.944031e-16 1.817868e-16 3.877971e-05 3.758736e-05
     [6] 3.701017e-05 3.690999e-05 3.625173e-05 3.706763e-05 3.786745e-05
     [11] 3.865142e-05 3.941974e-05 3.941974e-05 3.941974e-05 3.941974e-05
     [16] 3.941974e-05
     Error in process_opt_wts(wts_data_used, weights, nodes) :
     input 'weights' must be a data.table with 3 columns, two of which must be named as: 'ID' and 't'.
     In addition: Warning messages:
     1: glm.fit: algorithm did not converge
     2: glm.fit: algorithm did not converge
     3: glm.fit: algorithm did not converge
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -5.8682574 0.2154351 3.3021509 0.4033691 NA 0.7501467 NA
     [1] "Surv est: 0.983758322675102"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=0: 0.01624"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -4.67474313 0.19724908 2.21184261 -0.09839186 0.76483183 0.36869687
     TI.tminus1
     -0.98759997
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.48082464 0.25283340 2.46508499 0.04786835 NA -0.43706261
     TI.tminus1
     NA
     [1] "Surv est: 0.969902221464484"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=1: 0.0301"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.8073588 -1.1071567 1.3574257 -0.4540453 0.6083749 0.3767599 -1.4726757
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7570081 -0.3346276 1.4801253 -0.3532999 0.5055449 -0.5127511 -0.6589153
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.90325161 -0.07708853 2.01607750 -0.02829320 NA -0.32644563
     TI.tminus1
     NA
     [1] "Surv est: 0.953782240282528"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=2: 0.04622"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.2729961 0.6045142 2.3185601 -1.4506484 0.4525435 -1.0902410 -1.7027505
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.45925760 -0.49121038 1.40054082 -0.35287095 0.50934192 -0.02283871
     TI.tminus1
     -1.28687470
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8442520 -0.1010111 1.5056775 -0.2372471 0.4546915 -0.4782690 -0.6244729
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.94053966 0.04857403 1.99765895 0.01058704 NA -0.32554792
     TI.tminus1
     NA
     [1] "Surv est: 0.953681572539541"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04632"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.0863662 1.4415952 1.1242617 -0.4941329 -0.1391926 -0.8298997 -0.6156850
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1883548 1.2010569 1.3144619 -0.3947993 0.1333006 -0.9913184 -0.5170650
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.11978976 0.36019767 1.14780785 -0.23837798 0.37263297 -0.05869163
     TI.tminus1
     -0.85675524
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.6602088 0.3624027 1.3288288 -0.1996436 0.3619692 -0.4185487 -0.4804042
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.757594710 0.346812991 1.758549008 0.002438552 NA -0.302239540
     TI.tminus1
     NA
     [1] "Surv est: 0.943575229684676"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.05642"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.694637 0.368584 3.290803 -0.666631 NA NA NA
     [1] "tmle update: -0.00149135496809922"
     [1] "Surv est: 0.984107401301778"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=0: 0.01589"
     [1] "...empirical mean of the estimated EIC: -3.0907990045453e-05"
     [1] "...estimated TMLE variance: 2.41999050417123e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8004930 0.9282348 0.6879804 -0.5514791 0.7438655 NA NA
     [1] "tmle update: 0.0727160966327068"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6000572 0.5722892 2.2618565 -0.7563574 NA NA NA
     [1] "tmle update: -0.00223570491646532"
     [1] "Surv est: 0.969834495012909"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=1: 0.03017"
     [1] "...empirical mean of the estimated EIC: -6.07101133764973e-05"
     [1] "...estimated TMLE variance: 6.61356670225727e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9817186 -17.2807447 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595614761733"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715771607969"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470300657587"
     [1] "Surv est: 0.951909613102674"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=2: 0.04809"
     [1] "...empirical mean of the estimated EIC: -0.00010436571628225"
     [1] "...estimated TMLE variance: 0.000251078927354862"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595625433471"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715771369513"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470300648762"
     [1] "Surv est: 0.95190961310293"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04809"
     [1] "...empirical mean of the estimated EIC: -0.000104365720571851"
     [1] "...estimated TMLE variance: 0.000251078927359577"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.209019147885716"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8958776 0.4984205 0.7750137 1.4400473 0.1142727 NA NA
     [1] "tmle update: 0.0520880449204439"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1879874 -0.3427790 0.1064457 -0.4879009 0.5164562 NA NA
     [1] "tmle update: -0.0044898089735453"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7827815 0.1202478 0.3514419 -0.6841186 0.4586810 NA NA
     [1] "tmle update: 0.0158905661689564"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.4482301 0.1976754 1.4967452 -0.5174974 NA NA NA
     [1] "tmle update: -0.00227377143477277"
     [1] "Surv est: 0.925542187707399"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.07446"
     [1] "...empirical mean of the estimated EIC: -0.000520790968265632"
     [1] "...estimated TMLE variance: 0.00803708770988043"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595441256697"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715758304585"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.0033447030197795"
     [1] "Surv est: 0.951909613112289"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04809"
     [1] "...empirical mean of the estimated EIC: -1.65538533979758e-05"
     [1] "...estimated TMLE variance: 8.3806787779791e-06"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.209019147869959"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8958776 0.4984205 0.7750137 1.4400473 0.1142727 NA NA
     [1] "tmle update: 0.0520880449202842"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1879874 -0.3427790 0.1064457 -0.4879009 0.5164562 NA NA
     [1] "tmle update: -0.00448980955099559"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7827815 0.1202478 0.3514419 -0.6841186 0.4586810 NA NA
     [1] "tmle update: 0.0158905661764049"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.4482301 0.1976754 1.4967452 -0.5174974 NA NA NA
     [1] "tmle update: -0.00227377139578662"
     [1] "Surv est: 0.925542187729508"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.07446"
     [1] "...empirical mean of the estimated EIC: -8.12433860103577e-05"
     [1] "...estimated TMLE variance: 0.00019629047768188"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: 0.00455038396959827"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5351943 -0.2698513 0.0819634 -1.1897532 1.1194722 NA NA
     [1] "tmle update: 0.00148791277372818"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.9037005 0.1316045 1.9048099 -0.7888752 NA NA NA
     [1] "tmle update: 0.00387375452111821"
     [1] "Surv est: 0.952423126954576"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04758"
     [1] "...empirical mean of the estimated EIC: -3.11352727229608e-05"
     [1] "...estimated TMLE variance: 4.05438882728483e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.00435566075945477"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -5.1065413 0.4996280 0.7537557 1.4595663 0.1268353 NA NA
     [1] "tmle update: -6.23201904597049e-11"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.365723662 -0.465839994 0.005840225 -0.509288785 0.596038204 NA
     TI.tminus1
     NA
     [1] "tmle update: -4.44504971164046e-10"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.88176714 0.08310961 0.32781298 -0.75064933 0.51647978 NA
     TI.tminus1
     NA
     [1] "tmle update: 5.99583600832673e-11"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.5397115 0.1898817 1.5664979 -0.5505100 NA NA NA
     [1] "tmle update: 0.00279335492939026"
     [1] "Surv est: 0.931389922902869"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.06861"
     [1] "...empirical mean of the estimated EIC: -3.04000131367626e-05"
     [1] "...estimated TMLE variance: 5.41527268962014e-05"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -2.240428e-13 -9.163027e-14
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -4.661343e-14 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.830025e-13 -7.964050e-14
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     1.2490429 NA -0.4673254 -0.1775312
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.03015004 NA NA 0.01124218 -0.01120127
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -4.661343e-14 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.830025e-13 -7.964050e-14
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     1.2490429 NA -0.4673254 -0.1775312
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.03015004 NA NA 0.01124218 -0.01120127
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     done successfully.
    
    
    
     Executing test function test.speedglm.allestimators10Kdata ... [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     Timing stopped at: 49.72 1.559 58.8
     Error in readChar(con, 5L, useBytes = TRUE) : cannot open the connection
     In addition: Warning messages:
     1: glm.fit: algorithm did not converge
     2: glm.fit: algorithm did not converge
     3: glm.fit: algorithm did not converge
     4: glm.fit: algorithm did not converge
     5: glm.fit: algorithm did not converge
     6: glm.fit: algorithm did not converge
     7: glm.fit: algorithm did not converge
     8: glm.fit: algorithm did not converge
     9: In readChar(con, 5L, useBytes = TRUE) :
     cannot open compressed file '/tmp/Rtmpf_aaFf/sim.data.example.fup.Rd', probable reason 'No such file or directory'
     done successfully.
    
    
    
     Executing test function test.speedglm.stochastic.TMLE.NDE.1Kdata ... done successfully.
    
    
    
     Executing test function test.GCOMP.TMLE.10Kdata ... done successfully.
    
    
    
     Executing test function test.directRegressionDefn.10Kdata ... done successfully.
    
    
    
     Executing test function test.iterTMLE.10Kdata ... done successfully.
    
    
    
     Executing test function test.ContinModel ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "continA"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: continA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "ContinModel outcome: continA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: continA_B.1, continA_B.2, continA_B.3, continA_B.4, continA_B.5, continA_B.6, continA_B.7, continA_B.8, continA_B.9, continA_B.10, continA_B.11, continA_B.12, continA_B.13, continA_B.14, continA_B.15, continA_B.16, continA_B.17, continA_B.18, continA_B.19, continA_B.20, continA_B.21, continA_B.22, continA_B.23, continA_B.24, continA_B.25, continA_B.26, continA_B.27, continA_B.28, continA_B.29"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 29"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.4|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.5|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.6|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.7|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.8|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.9|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.10|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.11|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.12|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.13|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.14|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.15|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.16|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.17|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.18|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.19|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.20|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.21|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.22|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.23|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.24|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.25|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.26|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.27|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.28|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.29|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for continuous outcome: continA"
     [1] "freq counts by bin for continuous outcome: "
    
     2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
     519 518 518 518 518 518 518 518 518 518 518 518 518 519 518 518 518 518 518 518 518 518 518 518 518
     27 28
     518 519
     [1] "binned dataset: "
     continA_B.1 continA_B.2 continA_B.3 continA_B.4 continA_B.5 continA_B.6 continA_B.7
     [1,] 2 0 1 NA NA NA NA NA
     [2,] 10 0 0 0 0 0 0 0
     [3,] 26 0 0 0 0 0 0 0
     [4,] 19 0 0 0 0 0 0 0
     [5,] 28 0 0 0 0 0 0 0
     continA_B.8 continA_B.9 continA_B.10 continA_B.11 continA_B.12 continA_B.13 continA_B.14
     [1,] NA NA NA NA NA NA NA
     [2,] 0 0 1 NA NA NA NA
     [3,] 0 0 0 0 0 0 0
     [4,] 0 0 0 0 0 0 0
     [5,] 0 0 0 0 0 0 0
     continA_B.15 continA_B.16 continA_B.17 continA_B.18 continA_B.19 continA_B.20 continA_B.21
     [1,] NA NA NA NA NA NA NA
     [2,] NA NA NA NA NA NA NA
     [3,] 0 0 0 0 0 0 0
     [4,] 0 0 0 0 1 NA NA
     [5,] 0 0 0 0 0 0 0
     continA_B.22 continA_B.23 continA_B.24 continA_B.25 continA_B.26 continA_B.27 continA_B.28
     [1,] NA NA NA NA NA NA NA
     [2,] NA NA NA NA NA NA NA
     [3,] 0 0 0 0 1 NA NA
     [4,] NA NA NA NA NA NA NA
     [5,] 0 0 0 0 0 0 1
     continA_B.29
     [1,] NA
     [2,] NA
     [3,] NA
     [4,] NA
     [5,] NA
     [1] "fitting the model: P(continA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.656607e+01 -1.172459e-11 -1.310221e-11 -2.568646e-11
     [1] "fitting the model: P(continA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.23166549 -0.22366327 -0.09147569 0.02870292
     [1] "fitting the model: P(continA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.20800398 0.10907371 0.11333447 -0.09000571
     [1] "fitting the model: P(continA_B.4|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.22293347 -0.07810279 0.03215979 0.08561065
     [1] "fitting the model: P(continA_B.5|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.03669982 -0.28572550 -0.18262782 -0.07009494
     [1] "fitting the model: P(continA_B.6|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.088842749 0.001268752 -0.123778514 0.039248027
     [1] "fitting the model: P(continA_B.7|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.04038215 0.09890595 0.09480093 -0.06720914
     [1] "fitting the model: P(continA_B.8|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.93027754 -0.31059206 -0.08408421 -0.03566908
     [1] "fitting the model: P(continA_B.9|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.93201499 -0.02400097 0.17236632 -0.08908550
     [1] "fitting the model: P(continA_B.10|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.91974050 -0.08257696 0.01970503 0.06294592
     [1] "fitting the model: P(continA_B.11|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.84440410 -0.21962722 0.07776127 0.03268070
     [1] "fitting the model: P(continA_B.12|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.774824917 -0.079574389 0.002013999 0.019306822
     [1] "fitting the model: P(continA_B.13|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.71413971 -0.09412458 -0.11944369 0.07188333
     [1] "fitting the model: P(continA_B.14|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.659181998 -0.040062765 0.098554195 0.007595802
     [1] "fitting the model: P(continA_B.15|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.64531300 0.11013466 0.03465645 0.11392091
     [1] "fitting the model: P(continA_B.16|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.47351445 0.14283421 0.06998356 -0.08203588
     [1] "fitting the model: P(continA_B.17|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.43769438 0.33358661 0.02160913 -0.01351253
     [1] "fitting the model: P(continA_B.18|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.29886895 0.05469814 -0.13491354 0.02857818
     [1] "fitting the model: P(continA_B.19|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.185278546 -0.007623124 0.068518082 -0.047883543
     [1] "fitting the model: P(continA_B.20|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.12535797 -0.01735531 -0.04854580 0.10499538
     [1] "fitting the model: P(continA_B.21|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.989481148 0.147645106 0.120673747 0.003070492
     [1] "fitting the model: P(continA_B.22|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.797034915 -0.247430962 -0.007275464 0.057940516
     [1] "fitting the model: P(continA_B.23|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.56465313 -0.23222528 0.05357494 -0.06093729
     [1] "fitting the model: P(continA_B.24|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.31844495 -0.07720692 -0.20463875 -0.04140103
     [1] "fitting the model: P(continA_B.25|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -0.992014892 -0.297040477 0.009902895 -0.147228865
     [1] "fitting the model: P(continA_B.26|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -0.75843922 0.07022024 0.03527588 0.08908420
     [1] "fitting the model: P(continA_B.27|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.059798841 0.002692331 -0.109478106 -0.075660792
     [1] "fitting the model: P(continA_B.28|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656607e+01 -8.048931e-08 -5.052779e-06 -2.405891e-07
     [1] "fitting the model: P(continA_B.29|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for outcome continA succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for continuous outcome: continA"
     [1] "performing prediction for continuous outcome: continA"
     done successfully.
    
     ------------------- UNIT TEST SUMMARY ---------------------
    
     RUNIT TEST PROTOCOL -- Wed Apr 4 15:21:36 2018
     ***********************************************
     Number of test functions: 18
     Number of errors: 1
     Number of failures: 0
    
    
     1 Test Suite :
     stremr unit testing - 18 test functions, 1 error, 0 failures
     ERROR in test.speedglm.allestimators10Kdata: Error in readChar(con, 5L, useBytes = TRUE) : cannot open the connection
     Error:
    
     unit testing failed (#test failures: 0, #R errors: 1)
    
     Execution halted
Flavor: r-patched-solaris-x86

Version: 0.4
Check: tests
Result: ERROR
     Running ‘test-all.R’ [137s/178s]
    Running the tests in ‘tests/test-all.R’ failed.
    Complete output:
     > ## unit tests will not be done if RUnit is not available
     > # setwd("..")
     > # getwd()
     > # library(RUnit)
     > if(require("RUnit", quietly=TRUE)) {
     + ## --- Setup ---
     +
     + pkg <- "stremr" # <-- Tested package name
     +
     + if(Sys.getenv("RCMDCHECK") == "FALSE") {
     + ## Path to unit tests for standalone running under Makefile (not R CMD check)
     + ## PKG/tests/../inst/unitTests
     + # path <- file.path(getwd(), "..", "inst", "unitTests")
     + } else {
     + ## Path to unit tests for R CMD check
     + ## PKG.Rcheck/tests/../PKG/unitTests
     + # path <- system.file(package=pkg, "RUnit")
     +
     + # REPLACED WITH:
     + path <- file.path(getwd(), "RUnit")
     + }
     +
     + cat("\nRunning unit tests\n")
     + print(list(pkg=pkg, getwd=getwd(), pathToUnitTests=path))
     +
     + library(package=pkg, character.only=TRUE)
     +
     + ## If desired, load the name space to allow testing of private functions
     + ## if (is.element(pkg, loadedNamespaces()))
     + ## attach(loadNamespace(pkg), name=paste("namespace", pkg, sep=":"), pos=3)
     + ##
     + ## or simply call PKG:::myPrivateFunction() in tests
     +
     + ## --- Testing ---
     +
     + ## Define tests
     + test.suite <- defineTestSuite(name=paste(pkg, "unit testing"),
     + # dirs="./RUnit",
     + dirs=path,
     + testFileRegexp = "^RUnit_tests_+",
     + testFuncRegexp = "^test.+",
     + rngKind = "Marsaglia-Multicarry",
     + rngNormalKind = "Kinderman-Ramage")
     + ## Run
     + tests <- runTestSuite(test.suite)
     +
     + ## Default report name
     + pathReport <- file.path(path, "report")
     +
     + ## Report to stdout and text files
     + cat("------------------- UNIT TEST SUMMARY ---------------------\n\n")
     + printTextProtocol(tests, showDetails=FALSE)
     + printTextProtocol(tests, showDetails=FALSE,
     + fileName=paste0(pathReport, "Summary.txt"))
     + printTextProtocol(tests, showDetails=TRUE,
     + fileName=paste0(pathReport, ".txt"))
     + ## Report to HTML file
     + printHTMLProtocol(tests, fileName=paste0(pathReport, ".html"))
     +
     + ## Return stop() to cause R CMD check stop in case of
     + ## - failures i.e. FALSE to unit tests or
     + ## - errors i.e. R errors
     + tmp <- getErrors(tests)
     + if(tmp$nFail > 0 | tmp$nErr > 0) {
     + stop(paste("\n\nunit testing failed (#test failures: ", tmp$nFail,
     + ", #R errors: ", tmp$nErr, ")\n\n", sep=""))
     + }
     + } else {
     + warning("cannot run unit tests -- package RUnit is not available")
     + }
    
     Running unit tests
     $pkg
     [1] "stremr"
    
     $getwd
     [1] "/home/hornik/tmp/R.check/r-release-gcc/Work/PKGS/stremr.Rcheck/tests"
    
     $pathToUnitTests
     [1] "/home/hornik/tmp/R.check/r-release-gcc/Work/PKGS/stremr.Rcheck/tests/RUnit"
    
    
    
     Executing test function test.GenericModelPredict ... Loading required package: data.table
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.6829138 1.4512950 -0.4353432 0.5852046
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "catA"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: catA"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA, catA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "CategorModel outcome: catA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA_B.1, catA_B.2, catA_B.3"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "CategorModel outcome: catA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: catA_B.1, catA_B.2, catA_B.3"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for outcome based on stratified model for outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: catA"
     [1] "freq counts by bin for categorical outcome: "
    
     1 2 3
     4669 4657 4663
     [1] "binned dataset: "
     sA catA_B.1 catA_B.2 catA_B.3
     [1,] 3 NA 1 NA
     [2,] 1 NA 1 NA
     [3,] 1 NA 1 NA
     [4,] 1 NA 1 NA
     [5,] 2 NA 1 NA
     [1] "fitting the model: P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     [1] "fitting the model: P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -9.762950e-08 2.155173e-06 NA
     [1] "fitting the model: P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for catA var succeeded...
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: catA"
     [1] "freq counts by bin for categorical outcome: "
    
     1 2 3
     4669 4657 4663
     [1] "binned dataset: "
     sA catA_B.1 catA_B.2 catA_B.3
     [1,] 3 NA 1 NA
     [2,] 1 NA 1 NA
     [3,] 1 NA 1 NA
     [4,] 1 NA 1 NA
     [5,] 2 NA 1 NA
     [1] "fitting the model: P(catA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     [1] "fitting the model: P(catA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 -3.738646e-08 -2.346217e-07 -2.013073e-07
     [1] "fitting the model: P(catA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for catA var succeeded...
     fit for catA var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: catA"
     [1] "performing prediction for categorical outcome: catA"
     [1] "performing prediction for categorical outcome: catA"
     [1] "performing prediction for outcome based on stratified model: catA"
     [1] "performing prediction for categorical outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing prediction for categorical outcome: catA"
     making matrix for dummies for cat. censoring, reference category is 0
     done successfully.
    
    
    
     Executing test function test.Nsamp.n.test ... done successfully.
    
    
    
     Executing test function test.options ... [1] "Possible `stremr` options:"
     [1] "fit.package" "fit.algorithm" "bin.method"
     [4] "nbins" "maxncats" "maxNperBin"
     [7] "lower_bound_zero_Q" "skip_update_zero_Q"
     Error in stremrOptions("blahblah") :
     blahblah: this options does not exist
     Error in stremrOptions("blahblah", 5) : Invalid option name: blahblah
     Error in if (!(fit.algorithm %in% allowed.fit.algorithm)) stop("fit.algorithm must be one of: " %+% :
     argument is of length zero
     Error in set_all_stremr_options(fit.package = "speedglm", fit.algorithm = "blahblah", :
     fit.algorithm must be one of: glm, gbm, randomForest, deeplearning
     Error in set_all_stremr_options(fit.package = "blahblah", fit.algorithm = "glm", :
     fit.package must be one of: speedglm, glm, h2o
     Error in set_all_stremr_options(fit.package = "speedglm", fit.algorithm = "glm", :
     bin.method must be one of: equal.mass, equal.len, dhist
     $fit.package
     [1] "speedglm"
    
     $fit.algorithm
     [1] "glm"
    
     $bin.method
     [1] "equal.mass"
    
     $nbins
     [1] 10
    
     $maxncats
     [1] 20
    
     $maxNperBin
     [1] 500
    
     $lower_bound_zero_Q
     [1] TRUE
    
     $skip_update_zero_Q
     [1] TRUE
    
     done successfully.
    
    
    
     Executing test function test.regressionCases ... done successfully.
    
    
    
     Executing test function test.t.error ... done successfully.
    
    
    
     Executing test function test.DataStorageClass ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     Error in OData$get.outvar(var = "blah") :
     requested variable blah does not exist in DataStorageClass!
     done successfully.
    
    
    
     Executing test function test.error.fits.stratify ... Error in create_subset_expr(outvars = res$outvars, stratify.EXPRS = stratify.EXPRS) :
     Could not locate the appropriate regression variable(s) within the supplied stratification list stratify_CENS, stratify_TRT or stratify_MONITOR.
     The regression outcome variable(s) specified in gform_CENS, gform_TRT or gform_MONITOR were: ( 'C,TI' )
     However, the item names in the matching stratification list were: ( 'wrongC,TI,N' )
     done successfully.
    
    
    
     Executing test function test.helperfuns ... done successfully.
    
    
    
     Executing test function test.model.fits.stratify ... done successfully.
    
    
    
     Executing test function test.model.fits.categorCENSOR ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.52652066 0.05456581 0.10858685
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.19067146 NA 0.43343872 -0.01789425
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01340964 NA NA -0.03245807 -0.01185101
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 8.599825e-13 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.29183433 -0.07998923 0.03081559
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.64534186 NA 0.09366241 -0.16923766
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.01135495 NA NA -0.02269938 -0.01321850
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 1,t > 0 & C == 1)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 1"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 1"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 1 & TI == 1,t > 0 & C == 1 & TI == 1)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 1 & TI == 1"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 1 & TI == 1"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 8.599825e-13 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.29183433 -0.07998923 0.03081559
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     NA NA NA NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     NA 0.4924641 0.1270091 -0.1911502
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 1 & TI == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     NA NA NA NA NA
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 1 & TI == 1"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     NA NA NA NA NA
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     0.03161985 1.41249320 0.44869874 0.04224776
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: highA1c, lastNat1, C, TI"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,t > 0L & TI.tminus1 == 0L,t > 0L & TI.tminus1 == 1L)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 1L"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.52652066 0.05456581 0.10858685
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.64534186 NA 0.09366241 -0.16923766
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     -0.01467019 -0.45533330 NA NA NA
     [1] "fitting the model: P(N|highA1c, lastNat1, C, TI);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1 C TI
     -0.01135495 -0.02269938 -0.01321850 NA NA
     fit for N var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -21.2548627 0.9100488 2.1714524 19.1407169
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t > 0L & TI.tminus1 == 1L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 1.092843e-07 1.158713e-07 1.320318e-07
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "performing prediction for outcome based on stratified model: TI"
     done successfully.
    
    
    
     Executing test function test.model.fits.categorCENSOR2 ... Loading required package: magrittr
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "CatC"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: CatC"
     [1] "StratifiedModel expressions: (t < 16,t == 16)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC, CatC"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     ...fitting a model for categorical censoring...
     [1] "CategorModel outcome: CatC"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC_B.1, CatC_B.2, CatC_B.3"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.1|highA1c);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.2|highA1c);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.3|highA1c);\\ Stratify: t < 16"
     ...fitting a model for categorical censoring...
     [1] "CategorModel outcome: CatC"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: CatC_B.1, CatC_B.2, CatC_B.3"
     [1] "Predictors: highA1c"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.1|highA1c);\\ Stratify: t == 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.2|highA1c);\\ Stratify: t == 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(CatC_B.3|highA1c);\\ Stratify: t == 16"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L,(t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L),(t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L),(t > 0L) & (barTIm1eq0 == 1L))"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI, TI, TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L)"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L)"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (barTIm1eq0 == 1L)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: CatC"
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: CatC"
     [1] "freq counts by bin for categorical outcome: "
    
     0 1 2
     7469 347 314
     [1] "binned dataset: "
     sA CatC_B.1 CatC_B.2 CatC_B.3
     [1,] 0 0 0 NA
     [2,] 0 0 0 NA
     [3,] 1 1 NA NA
     [4,] 0 0 0 NA
     [5,] 0 0 0 NA
     [1] "fitting the model: P(CatC_B.1|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -3.1487960 0.1616531
     [1] "fitting the model: P(CatC_B.2|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -3.13719779 -0.08098814
     [1] "fitting the model: P(CatC_B.3|highA1c);\\ Stratify: t < 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     NA NA
     fit for CatC var succeeded...
     making matrix for dummies for cat. censoring, reference category is 0
     [1] "performing fitting for categorical outcome: CatC"
     [1] "freq counts by bin for categorical outcome: "
    
     0 1 2
     7469 347 314
     [1] "binned dataset: "
     sA CatC_B.1 CatC_B.2 CatC_B.3
     [1,] 0 0 0 NA
     [2,] 0 0 0 NA
     [3,] 1 1 NA NA
     [4,] 0 0 0 NA
     [5,] 0 0 0 NA
     [1] "fitting the model: P(CatC_B.1|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -2.9593646 0.5614693
     [1] "fitting the model: P(CatC_B.2|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     -4.89784 -15.66823
     [1] "fitting the model: P(CatC_B.3|highA1c);\\ Stratify: t == 16"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c
     NA NA
     fit for CatC var succeeded...
     fit for CatC var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: t == 0L"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.156898 2.117370 2.269857 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 1L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.1141458 0.9100488 2.1714524 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (N.tminus1 == 0L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.656607e+01 2.444839e-12 2.082888e-12 NA
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: (t > 0L) & (barTIm1eq0 == 1L)"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -21.2548627 0.9100488 2.1714524 19.1407169
     fit for TI var succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.02436859
     [1] "performing prediction for outcome based on stratified model: CatC"
     [1] "performing prediction for categorical outcome: CatC"
     [1] "performing prediction for categorical outcome: CatC"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "N"
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     done successfully.
    
    
    
     Executing test function test.buildingblocks ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     Error in getIPWeights(OData = OData, intervened_TRT = "TI.set1", rule_name = "TI1") :
     ...cannot locate propensity scores in 'OData' object - must run fitPropensity(...) prior to calling this function
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t < 16,t == 16)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t < 16"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 16"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t < 16"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.198768e-13 -5.125570e-14
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 16"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -6.143963e-14 -2.839781e-14
     fit for C var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "performing estimation for the following TRT/MONITOR rules found in column 'rule.name': TI0,TI1"
     [1] "periods"
     [1] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
     [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     [1] "Periods.0to0_TI0"
     [1] "Periods.1to1_TI0"
     [1] "Periods.2to2_TI0"
     [1] "Periods.3to3_TI0"
     [1] "Periods.4to4_TI0"
     [1] "Periods.5to5_TI0"
     [1] "Periods.6to6_TI0"
     [1] "Periods.7to7_TI0"
     [1] "Periods.8to11_TI0"
     [1] "Periods.12to15_TI0"
     [1] "Periods.0to0_TI1"
     [1] "Periods.1to1_TI1"
     [1] "Periods.2to2_TI1"
     [1] "Periods.3to3_TI1"
     [1] "Periods.4to4_TI1"
     [1] "Periods.5to5_TI1"
     [1] "Periods.6to6_TI1"
     [1] "Periods.7to7_TI1"
     [1] "Periods.8to11_TI1"
     [1] "Periods.12to15_TI1"
     ...fitting hazard MSM with speedglm::speedglm.wfit...
     [1] "MSM fits"
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     -5.465039e+00 -4.324378e+00 -4.012934e+00 -1.166619e+15
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     -6.871355e+14 -4.884654e+14 -6.732368e+00 -6.414551e+00
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     -2.490327e+15 -3.057464e+15 -3.089228e+00 -4.070768e+00
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     -4.097356e+00 -1.444049e+01 -3.626218e+00 -4.172158e+00
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     -5.928687e+00 -3.921940e+00 -4.645602e+00 -3.410729e+00
     ...evaluating MSM-based survival curves...
     ...evaluating SEs based on MSM hazard fit and the estimated IC...
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     9.379699e-17 2.900859e-16 7.383396e-15 7.293270e+00
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     6.561300e+01 4.445403e+02 3.220105e-14 2.800474e-14
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.030033e+02 7.899748e+02 7.913397e-18 2.865011e-18
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     7.009244e-18 4.879654e-08 1.399031e-19 7.292022e-18
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     2.532557e-18 1.471364e-17 3.615109e-16 1.717254e-15
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     9.340525e-15 3.126553e-15 1.800440e-14 3.336980e+14
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     7.563694e+14 1.183848e+15 5.560005e-15 5.426432e-15
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     1.830248e+14 5.408850e+14 4.968619e-15 3.569094e-15
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     6.622362e-15 1.000001e+00 8.253617e-17 2.682887e-15
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     3.708932e-15 2.085976e-15 9.255499e-15 3.032843e-15
     [1] "Should all be very small: "
     [1] 3.953818e-17 7.916801e-17 2.288376e-16 2.288376e-16 2.288376e-16
     [6] 2.288376e-16 2.227361e-16 2.339417e-16 2.339417e-16 2.339417e-16
     [11] 2.339417e-16 2.339417e-16 2.339417e-16 2.339417e-16 2.339417e-16
     [16] 2.339417e-16
     [1] "Should all be very small: "
     [1] 2.087237e-16 2.567391e-16 1.552191e-16 4.951408e-07 4.823035e-07
     [6] 4.749798e-07 4.737188e-07 4.645200e-07 4.601013e-07 4.557247e-07
     [11] 4.513896e-07 4.470959e-07 4.328058e-07 4.189726e-07 4.055814e-07
     [16] 3.926183e-07
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -2.240428e-13 -9.163027e-14
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "performing estimation for the following TRT/MONITOR rules found in column 'rule.name': TI0,TI1"
     [1] "periods"
     [1] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
     [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     [1] "Periods.0to0_TI0"
     [1] "Periods.1to1_TI0"
     [1] "Periods.2to2_TI0"
     [1] "Periods.3to3_TI0"
     [1] "Periods.4to4_TI0"
     [1] "Periods.5to5_TI0"
     [1] "Periods.6to6_TI0"
     [1] "Periods.7to7_TI0"
     [1] "Periods.8to11_TI0"
     [1] "Periods.12to15_TI0"
     [1] "Periods.0to0_TI1"
     [1] "Periods.1to1_TI1"
     [1] "Periods.2to2_TI1"
     [1] "Periods.3to3_TI1"
     [1] "Periods.4to4_TI1"
     [1] "Periods.5to5_TI1"
     [1] "Periods.6to6_TI1"
     [1] "Periods.7to7_TI1"
     [1] "Periods.8to11_TI1"
     [1] "Periods.12to15_TI1"
     ...fitting hazard MSM with speedglm::speedglm.wfit...
     [1] "MSM fits"
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     -5.479625e+00 -4.224521e+15 -4.040682e+15 -3.195295e+15
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     -3.082898e+15 -2.778817e+15 -3.052026e+15 -3.796228e+15
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     -2.715406e+15 -1.534193e+15 -3.048470e+00 -4.020852e+00
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     -4.106498e+00 -1.007712e+01 -3.450746e+00 -4.160778e+00
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     -5.909203e+00 -4.008647e+00 -4.781623e+00 -3.422484e+15
     ...evaluating MSM-based survival curves...
     ...evaluating SEs based on MSM hazard fit and the estimated IC...
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     1.363995e-15 3.892340e+00 1.153066e+02 3.014492e+03
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     2.096739e+04 2.100000e+04 1.300000e+04 5.000000e+03
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.700000e+04 1.000000e+04 2.218218e-17 1.992734e-17
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     1.087903e-17 1.670762e-05 2.380815e-17 8.984546e-17
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     4.050727e-18 8.676045e-17 3.446043e-04 2.159757e+02
     [1] "Should all be very small: "
     Periods.0to0_TI0 Periods.1to1_TI0 Periods.2to2_TI0 Periods.3to3_TI0
     2.012238e-14 5.581563e+13 7.715289e+13 2.180508e+14
     Periods.4to4_TI0 Periods.5to5_TI0 Periods.6to6_TI0 Periods.7to7_TI0
     2.367837e+14 2.874638e+14 2.419289e+14 1.178953e+14
     Periods.8to11_TI0 Periods.12to15_TI0 Periods.0to0_TI1 Periods.1to1_TI1
     2.980323e+14 4.949011e+14 9.314984e-15 1.161900e-14
     Periods.2to2_TI1 Periods.3to3_TI1 Periods.4to4_TI1 Periods.5to5_TI1
     3.404072e-15 1.000042e+00 9.042079e-16 3.580885e-15
     Periods.6to6_TI1 Periods.7to7_TI1 Periods.8to11_TI1 Periods.12to15_TI1
     4.712621e-16 6.766642e-16 1.571325e-04 1.801860e+14
     [1] "Should all be very small: "
     [1] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [6] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [11] 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17 8.330934e-17
     [16] 8.330934e-17
     [1] "Should all be very small: "
     [1] 3.999902e-16 2.024836e-16 2.525296e-16 3.877971e-05 3.758736e-05
     [6] 3.701017e-05 3.690999e-05 3.625173e-05 3.706763e-05 3.786745e-05
     [11] 3.865142e-05 3.941974e-05 3.941974e-05 3.941974e-05 3.941974e-05
     [16] 3.941974e-05
     Error in process_opt_wts(wts_data_used, weights, nodes) :
     input 'weights' must be a data.table with 3 columns, two of which must be named as: 'ID' and 't'.
     In addition: Warning messages:
     1: glm.fit: algorithm did not converge
     2: glm.fit: algorithm did not converge
     3: glm.fit: algorithm did not converge
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -5.8682574 0.2154351 3.3021509 0.4033691 NA 0.7501467 NA
     [1] "Surv est: 0.983758322675102"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=0: 0.01624"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -4.67474313 0.19724908 2.21184261 -0.09839186 0.76483183 0.36869687
     TI.tminus1
     -0.98759997
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.48082464 0.25283340 2.46508499 0.04786835 NA -0.43706261
     TI.tminus1
     NA
     [1] "Surv est: 0.969902221464484"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=1: 0.0301"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.8073588 -1.1071567 1.3574257 -0.4540453 0.6083749 0.3767599 -1.4726757
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7570081 -0.3346276 1.4801253 -0.3532999 0.5055449 -0.5127511 -0.6589153
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.90325161 -0.07708853 2.01607750 -0.02829320 NA -0.32644563
     TI.tminus1
     NA
     [1] "Surv est: 0.953782240282527"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=2: 0.04622"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.2729961 0.6045142 2.3185601 -1.4506484 0.4525435 -1.0902410 -1.7027505
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.45925760 -0.49121038 1.40054082 -0.35287095 0.50934192 -0.02283871
     TI.tminus1
     -1.28687470
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8442520 -0.1010111 1.5056775 -0.2372471 0.4546915 -0.4782690 -0.6244729
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.94053966 0.04857403 1.99765895 0.01058704 NA -0.32554792
     TI.tminus1
     NA
     [1] "Surv est: 0.953681572539541"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04632"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi FALSE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi FALSE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.0863662 1.4415952 1.1242617 -0.4941329 -0.1391926 -0.8298997 -0.6156850
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1883548 1.2010569 1.3144619 -0.3947993 0.1333006 -0.9913184 -0.5170650
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.11978976 0.36019767 1.14780785 -0.23837798 0.37263297 -0.05869163
     TI.tminus1
     -0.85675524
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.6602088 0.3624027 1.3288288 -0.1996436 0.3619692 -0.4185487 -0.4804042
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.757594710 0.346812991 1.758549008 0.002438552 NA -0.302239540
     TI.tminus1
     NA
     [1] "Surv est: 0.943575229684677"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.05642"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.694637 0.368584 3.290803 -0.666631 NA NA NA
     [1] "tmle update: -0.00149135496809919"
     [1] "Surv est: 0.984107401301778"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=0: 0.01589"
     [1] "...empirical mean of the estimated EIC: -3.09079900454493e-05"
     [1] "...estimated TMLE variance: 2.41999050417123e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8004930 0.9282348 0.6879804 -0.5514791 0.7438655 NA NA
     [1] "tmle update: 0.0727160966327068"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6000572 0.5722892 2.2618565 -0.7563574 NA NA NA
     [1] "tmle update: -0.0022357049164653"
     [1] "Surv est: 0.969834495012909"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=1: 0.03017"
     [1] "...empirical mean of the estimated EIC: -6.07101133764977e-05"
     [1] "...estimated TMLE variance: 6.61356670225727e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9817186 -17.2807447 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595614761723"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715771607933"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470300657529"
     [1] "Surv est: 0.951909613102674"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=2: 0.04809"
     [1] "...empirical mean of the estimated EIC: -0.00010436571628225"
     [1] "...estimated TMLE variance: 0.000251078927354862"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.00489595625433471"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715771369513"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470300648418"
     [1] "Surv est: 0.95190961310293"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04809"
     [1] "...empirical mean of the estimated EIC: -0.000104365720571848"
     [1] "...estimated TMLE variance: 0.000251078927359577"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.209019147885717"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8958776 0.4984205 0.7750137 1.4400473 0.1142727 NA NA
     [1] "tmle update: 0.0520880449204392"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1879874 -0.3427790 0.1064457 -0.4879009 0.5164562 NA NA
     [1] "tmle update: -0.00448980897354264"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7827815 0.1202478 0.3514419 -0.6841186 0.4586810 NA NA
     [1] "tmle update: 0.0158905661689546"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.4482301 0.1976754 1.4967452 -0.5174974 NA NA NA
     [1] "tmle update: -0.00227377143477276"
     [1] "Surv est: 0.925542187707399"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.07446"
     [1] "...empirical mean of the estimated EIC: -0.000520790968265705"
     [1] "...estimated TMLE variance: 0.00803708770988044"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: -0.0048959544125669"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5420862 -0.2635159 0.0856417 -1.1860831 1.1179562 NA NA
     [1] "tmle update: 0.0333715758304584"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.8806788 0.1306788 1.8884045 -0.7910252 NA NA NA
     [1] "tmle update: -0.00334470301977723"
     [1] "Surv est: 0.951909613112289"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04809"
     [1] "...empirical mean of the estimated EIC: -1.65538533979754e-05"
     [1] "...estimated TMLE variance: 8.3806787779791e-06"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.209019147869959"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -4.8958776 0.4984205 0.7750137 1.4400473 0.1142727 NA NA
     [1] "tmle update: 0.0520880449202836"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.1879874 -0.3427790 0.1064457 -0.4879009 0.5164562 NA NA
     [1] "tmle update: -0.00448980955099783"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.7827815 0.1202478 0.3514419 -0.6841186 0.4586810 NA NA
     [1] "tmle update: 0.0158905661764066"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.4482301 0.1976754 1.4967452 -0.5174974 NA NA NA
     [1] "tmle update: -0.00227377139578826"
     [1] "Surv est: 0.925542187729508"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.07446"
     [1] "...empirical mean of the estimated EIC: -8.12433860103523e-05"
     [1] "...estimated TMLE variance: 0.00019629047768188"
     ...evaluating IPWeights for TMLE...
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 4"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1
     -2.656607e+01 -2.363684e-14 -1.874001e-14 -2.747293e-14 9.552227e-15
     TI TI.tminus1
     NA NA
     [1] "tmle update: 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -5.1764346 -17.9785757 -17.2777471 -0.6408232 1.6792590 NA
     TI.tminus1
     NA
     [1] "tmle update: 0.00455038396959821"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.5351943 -0.2698513 0.0819634 -1.1897532 1.1194722 NA NA
     [1] "tmle update: 0.00148791277372786"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.9037005 0.1316045 1.9048099 -0.7888752 NA NA NA
     [1] "tmle update: 0.0038737545211174"
     [1] "Surv est: 0.952423126954576"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=3: 0.04758"
     [1] "...empirical mean of the estimated EIC: -3.11352727229658e-05"
     [1] "...estimated TMLE variance: 4.05438882728483e-05"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "t == 4" "t == 3" "t == 2" "t == 1" "t == 0"
     [1] "Outcomes: "
     [1] "Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1,Q.kplus1"
     [1] "No. of regressions: 5"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 4"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 5
     $ t_period : int 4
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 4"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 3"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 4
     $ t_period : int 3
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 3"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 2"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 3
     $ t_period : int 2
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 2"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 1"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 2
     $ t_period : int 1
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 1"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: Q.kplus1"
     [1] "Predictors: CVD, highA1c, N, lastNat1, TI, TI.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of QlearnModel :"
     [1] "P(Q.kplus1|CVD, highA1c, N, lastNat1, TI, TI.tminus1);\\ Stratify: t == 0"
     [1] "initialized Q class"
     List of 15
     $ Qreg_counter : int 1
     $ t_period : int 0
     $ TMLE : logi TRUE
     $ outvar : chr "Q.kplus1"
     $ predvars : chr [1:6] "CVD" "highA1c" "N" "lastNat1" ...
     $ outvar.class : chr "Qlearn"
     $ subset_vars : chr "Q.kplus1"
     $ subset_exprs : chr "t == 0"
     $ subset_censored : NULL
     $ stratifyQ_by_rule : logi TRUE
     $ lower_bound_zero_Q: logi TRUE
     $ regimen_names : logi NA
     $ pool_regimes : logi FALSE
     $ model_contrl :List of 1
     ..$ distribution: chr "gaussian"
     $ censoring : logi FALSE
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -3.6781561 0.8302792 2.3040444 -1.0845762 -0.9213487 NA NA
     [1] "tmle update: 0.0043556607594549"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -5.1065413 0.4996280 0.7537557 1.4595663 0.1268353 NA NA
     [1] "tmle update: -6.23198919478809e-11"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -3.365723662 -0.465839994 0.005840225 -0.509288785 0.596038204 NA
     TI.tminus1
     NA
     [1] "tmle update: -4.44506521637441e-10"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI
     -2.88176714 0.08310961 0.32781298 -0.75064933 0.51647978 NA
     TI.tminus1
     NA
     [1] "tmle update: 5.99566016142493e-11"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N lastNat1 TI TI.tminus1
     -2.5397115 0.1898817 1.5664979 -0.5505100 NA NA NA
     [1] "tmle update: 0.0027933549293886"
     [1] "Surv est: 0.931389922902869"
     [1] "No. of obs for last prediction of Q: 1000"
     [1] "EY^* estimate at t=4: 0.06861"
     [1] "...empirical mean of the estimated EIC: -3.04000131367507e-05"
     [1] "...estimated TMLE variance: 5.41527268962014e-05"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -2.240428e-13 -9.163027e-14
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "TI"
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -4.661343e-14 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.830025e-13 -7.964050e-14
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     1.2490429 NA -0.4673254 -0.1775312
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.03015004 NA NA 0.01124218 -0.01120127
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "glm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "StratifiedModel outcome: C"
     [1] "StratifiedModel expressions: (t == 0L,t > 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, C"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "StratifiedModel outcome: TI"
     [1] "StratifiedModel expressions: (t == 0L & C == 0,t > 0 & C == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI, TI"
     [1] "Predictors: C, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "StratifiedModel outcome: N"
     [1] "StratifiedModel expressions: (t == 0L & C == 0 & TI == 0,t > 0 & C == 0 & TI == 0)"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N, N"
     [1] "Predictors: C, TI, highA1c, lastNat1"
     [1] "No. of regressions: 2"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "TI"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: TI"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "performing fitting for outcome based on stratified model for outcome: C"
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t == 0L"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -4.661343e-14 NA
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: t > 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 -1.830025e-13 -7.964050e-14
     fit for C var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: TI"
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     -1.816513 NA 2.835083 NA
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C highA1c lastNat1
     1.2490429 NA -0.4673254 -0.1775312
     fit for TI var succeeded...
     [1] "performing fitting for outcome based on stratified model for outcome: N"
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t == 0L & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.01467019 NA NA -0.45533330 NA
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: t > 0 & C == 0 & TI == 0"
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept C TI highA1c lastNat1
     -0.03015004 NA NA 0.01124218 -0.01120127
     fit for N var succeeded...
     [1] "fitting the model: P(TI|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept CVD highA1c N.tminus1
     0.6250400 1.3852271 -0.1432429 0.1288901
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling glm.fit..."
     [1] "glm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for outcome based on stratified model: C"
     [1] "performing prediction for outcome based on stratified model: TI"
     [1] "performing prediction for outcome based on stratified model: N"
     done successfully.
    
    
    
     Executing test function test.speedglm.allestimators10Kdata ... [1] "defined t.dummy: Periods.0to0"
     [1] "defined t.dummy: Periods.1to1"
     [1] "defined t.dummy: Periods.2to2"
     [1] "defined t.dummy: Periods.3to3"
     [1] "defined t.dummy: Periods.4to4"
     [1] "defined t.dummy: Periods.5to5"
     [1] "defined t.dummy: Periods.6to6"
     [1] "defined t.dummy: Periods.7to7"
     [1] "defined t.dummy: Periods.8to11"
     [1] "defined t.dummy: Periods.12to15"
     writing report to directory: /tmp/RtmprPfFMF
     writing related figures to report subdirectory: figure.sim.data.example.fup2
    
    
     processing file: /tmp/RtmprPfFMF/report-script-rmd.spin.Rmd
     inline R code fragments
    
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     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmprPfFMF/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmprPfFMF/sim.data.example.fup2.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-release-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmprPfFMF/rmarkdown-str7891a7a2b4f.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup2.html
     writing report to directory: /tmp/RtmprPfFMF
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmprPfFMF/report-script-rmd.spin.Rmd
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     output file: /tmp/RtmprPfFMF/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmprPfFMF/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmprPfFMF/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-release-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmprPfFMF/rmarkdown-str789812375.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmprPfFMF
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmprPfFMF/report-script-rmd.spin.Rmd
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     $ echo: logi FALSE
    
     label: unnamed-chunk-7 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-8 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-9 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /tmp/RtmprPfFMF/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmprPfFMF/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmprPfFMF/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-release-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmprPfFMF/rmarkdown-str7893187154c.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmprPfFMF
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmprPfFMF/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-3 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-4 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     label: unnamed-chunk-5 (with options)
     List of 1
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-7 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-8 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-9 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /tmp/RtmprPfFMF/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmprPfFMF/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmprPfFMF/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-release-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmprPfFMF/rmarkdown-str78940848f50.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmprPfFMF
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmprPfFMF/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-3 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-4 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     label: unnamed-chunk-5 (with options)
     List of 1
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-7 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-8 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-9 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /tmp/RtmprPfFMF/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmprPfFMF/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmprPfFMF/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-release-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmprPfFMF/rmarkdown-str7893d4560b.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmprPfFMF
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmprPfFMF/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-3 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-4 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     label: unnamed-chunk-5 (with options)
     List of 1
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-7 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-8 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-9 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /tmp/RtmprPfFMF/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmprPfFMF/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmprPfFMF/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-release-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmprPfFMF/rmarkdown-str7895c41ebd1.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
     writing report to directory: /tmp/RtmprPfFMF
     writing related figures to report subdirectory: figure.sim.data.example.fup
    
    
     processing file: /tmp/RtmprPfFMF/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-3 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-4 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     label: unnamed-chunk-5 (with options)
     List of 1
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-7 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-8 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-9 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-11 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /tmp/RtmprPfFMF/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmprPfFMF/report-script-rmd.utf8.md --to html4 --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmprPfFMF/sim.data.example.fup.html --smart --email-obfuscation none --self-contained --standalone --section-divs --table-of-contents --toc-depth 3 --variable toc_float=1 --variable toc_selectors=h1,h2,h3 --variable toc_collapsed=1 --variable toc_smooth_scroll=1 --variable toc_print=1 --template /home/hornik/tmp/R.check/r-release-gcc/Work/build/Packages/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --number-sections --variable 'theme:bootstrap' --include-in-header /tmp/RtmprPfFMF/rmarkdown-str78979e78e1c.html --mathjax --variable 'mathjax-url:https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
    
     Output created: sim.data.example.fup.html
    
    
     processing file: /tmp/RtmprPfFMF/report-script-rmd.spin.Rmd
     inline R code fragments
    
     label: setup (with options)
     List of 1
     $ include: logi FALSE
    
     label: unnamed-chunk-1 (with options)
     List of 2
     $ echo : logi FALSE
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-2 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-3 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-4 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     label: unnamed-chunk-5 (with options)
     List of 1
     $ include: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-6 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-7 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-8 (with options)
     List of 1
     $ echo: logi FALSE
    
     label: unnamed-chunk-9 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-10 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with IPW-Adjusted KM.\\label{fig:survPlotGCOMP}"
    
     !!! Error: Cannot write tmp file `tmp-pdfcrop-2298.tex' (Read-only file system)!
     label: unnamed-chunk-11 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-12 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "Survival with KM.\\label{fig:survPlotGCOMP}"
    
     inline R code fragments
    
     label: unnamed-chunk-13 (with options)
     List of 1
     $ echo: logi FALSE
    
     inline R code fragments
    
     label: unnamed-chunk-14 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "IPW-MSM Survival.\\label{fig:survPlotIPW}"
    
     !!! Error: Cannot write tmp file `tmp-pdfcrop-2618.tex' (Read-only file system)!
     inline R code fragments
    
     label: unnamed-chunk-15 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-16 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "G-Computation Survival.\\label{fig:survPlotGCOMP}"
    
     label: unnamed-chunk-17 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     inline R code fragments
    
     label: unnamed-chunk-18 (with options)
     List of 4
     $ echo : logi FALSE
     $ fig.width : num 5
     $ fig.height: num 5
     $ fig.cap : chr "TMLE Survival.\\label{fig:survPlotTMLE}"
    
     !!! Error: Cannot write tmp file `tmp-pdfcrop-2781.tex' (Read-only file system)!
     inline R code fragments
    
     label: unnamed-chunk-19 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     label: unnamed-chunk-20 (with options)
     List of 2
     $ echo : logi FALSE
     $ results: chr "asis"
    
     ordinary text without R code
    
     output file: /tmp/RtmprPfFMF/report-script-rmd.knit.md
    
     /usr/bin/pandoc +RTS -K512m -RTS /tmp/RtmprPfFMF/report-script-rmd.utf8.md --to latex --from markdown+autolink_bare_uris+ascii_identifiers+tex_math_single_backslash+escaped_line_breaks --output /tmp/RtmprPfFMF/sim.data.example.fup.tex --table-of-contents --toc-depth 2 --template /home/hornik/tmp/R.check/r-release-gcc/Work/build/Packages/rmarkdown/rmd/latex/default-1.17.0.2.tex --number-sections --highlight-style tango --latex-engine pdflatex --variable graphics=yes --variable 'geometry:margin=1in'
     You are recommended to install the tinytex package to build PDF.FALSE
     Latexmk: This is Latexmk, John Collins, 1 January 2015, version: 4.41.
     Cannot write file 'sim.data.example.fup.aux'
    
     Latexmk, John Collins, 1 January 2015. Version 4.41
     Timing stopped at: 42.26 1.914 58.93
     Error in make_report_rmd(OData, NPMSM = list(surv1, surv2), MSM = MSM.IPAW, :
     Failed to compile /tmp/RtmprPfFMF/sim.data.example.fup.tex.
     done successfully.
    
    
    
     Executing test function test.speedglm.stochastic.TMLE.NDE.1Kdata ... done successfully.
    
    
    
     Executing test function test.GCOMP.TMLE.10Kdata ... done successfully.
    
    
    
     Executing test function test.directRegressionDefn.10Kdata ... done successfully.
    
    
    
     Executing test function test.iterTMLE.10Kdata ... done successfully.
    
    
    
     Executing test function test.ContinModel ... [1] "Using the following stremr options/settings: "
    
     List of 8
     $ fit.package : chr "speedglm"
     $ fit.algorithm : chr "glm"
     $ bin.method : chr "equal.mass"
     $ nbins : num 10
     $ maxncats : num 20
     $ maxNperBin : num 500
     $ lower_bound_zero_Q: logi TRUE
     $ skip_update_zero_Q: logi TRUE
     [1] "...detecting the type of each input column..."
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "gC" "gA" "gN"
     [1] "Outcomes: "
     [1] ""
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "C,TI,N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: C, TI, N"
     [1] "Predictors: highA1c, lastNat1"
     [1] "No. of regressions: 3"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "continA"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: continA"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "ContinModel outcome: continA"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: continA_B.1, continA_B.2, continA_B.3, continA_B.4, continA_B.5, continA_B.6, continA_B.7, continA_B.8, continA_B.9, continA_B.10, continA_B.11, continA_B.12, continA_B.13, continA_B.14, continA_B.15, continA_B.16, continA_B.17, continA_B.18, continA_B.19, continA_B.20, continA_B.21, continA_B.22, continA_B.23, continA_B.24, continA_B.25, continA_B.26, continA_B.27, continA_B.28, continA_B.29"
     [1] "Predictors: CVD, highA1c, N.tminus1"
     [1] "No. of regressions: 29"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.4|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.5|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.6|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.7|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.8|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.9|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.10|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.11|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.12|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.13|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.14|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.15|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.16|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.17|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.18|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.19|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.20|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.21|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.22|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.23|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.24|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.25|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.26|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.27|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.28|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(continA_B.29|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "...ListOfRegressionForms..."
     [1] "Outcomes: "
     [1] "N"
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? FALSE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of GenericModel:"
     [1] "#----------------------------------------------------------------------------------"
     [1] "Outcomes: N"
     [1] "Predictors: "
     [1] "No. of regressions: 1"
     [1] "All outcomes binary? TRUE"
     [1] "#----------------------------------------------------------------------------------"
     [1] "New instance of BinaryOutcomeModel :"
     [1] "P(N|);\\ Stratify: "
     [1] "fitting the model: P(C|highA1c, lastNat1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept highA1c lastNat1
     -2.656607e+01 9.238692e-12 2.688942e-12
     [1] "fitting the model: P(TI|C, highA1c, lastNat1);\\ Stratify: C == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C highA1c lastNat1
     0.87385792 NA -0.18986136 -0.06706656
     [1] "fitting the model: P(N|C, TI, highA1c, lastNat1);\\ Stratify: C == 0 & TI == 0"
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept C TI highA1c lastNat1
     -0.025688525 NA NA 0.001591313 -0.012014026
     [1] "performing fitting for continuous outcome: continA"
     [1] "freq counts by bin for continuous outcome: "
    
     2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
     519 518 518 518 518 518 518 518 518 518 518 518 518 519 518 518 518 518 518 518 518 518 518 518 518
     27 28
     518 519
     [1] "binned dataset: "
     continA_B.1 continA_B.2 continA_B.3 continA_B.4 continA_B.5 continA_B.6 continA_B.7
     [1,] 21 0 0 0 0 0 0 0
     [2,] 10 0 0 0 0 0 0 0
     [3,] 28 0 0 0 0 0 0 0
     [4,] 17 0 0 0 0 0 0 0
     [5,] 4 0 0 0 1 NA NA NA
     continA_B.8 continA_B.9 continA_B.10 continA_B.11 continA_B.12 continA_B.13 continA_B.14
     [1,] 0 0 0 0 0 0 0
     [2,] 0 0 1 NA NA NA NA
     [3,] 0 0 0 0 0 0 0
     [4,] 0 0 0 0 0 0 0
     [5,] NA NA NA NA NA NA NA
     continA_B.15 continA_B.16 continA_B.17 continA_B.18 continA_B.19 continA_B.20 continA_B.21
     [1,] 0 0 0 0 0 0 1
     [2,] NA NA NA NA NA NA NA
     [3,] 0 0 0 0 0 0 0
     [4,] 0 0 1 NA NA NA NA
     [5,] NA NA NA NA NA NA NA
     continA_B.22 continA_B.23 continA_B.24 continA_B.25 continA_B.26 continA_B.27 continA_B.28
     [1,] NA NA NA NA NA NA NA
     [2,] NA NA NA NA NA NA NA
     [3,] 0 0 0 0 0 0 1
     [4,] NA NA NA NA NA NA NA
     [5,] NA NA NA NA NA NA NA
     continA_B.29
     [1,] NA
     [2,] NA
     [3,] NA
     [4,] NA
     [5,] NA
     [1] "fitting the model: P(continA_B.1|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.656607e+01 -1.172459e-11 -1.310221e-11 -2.568646e-11
     [1] "fitting the model: P(continA_B.2|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.35296269 0.05840155 0.15391935 0.10583906
     [1] "fitting the model: P(continA_B.3|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.20883212 0.19545935 -0.07429263 -0.03621939
     [1] "fitting the model: P(continA_B.4|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.231971451 0.004434272 0.086978497 0.065624484
     [1] "fitting the model: P(continA_B.5|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.13559540 0.29851267 -0.00227520 -0.06901207
     [1] "fitting the model: P(continA_B.6|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.06903375 -0.14292454 -0.00180812 -0.01393547
     [1] "fitting the model: P(continA_B.7|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.01628268 -0.07461437 0.06514641 -0.06449627
     [1] "fitting the model: P(continA_B.8|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -3.01459276 -0.19439665 0.08520062 0.03828360
     [1] "fitting the model: P(continA_B.9|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.87841908 0.03242339 -0.03415432 -0.12168506
     [1] "fitting the model: P(continA_B.10|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.92107566 -0.31591865 -0.04467733 0.12681822
     [1] "fitting the model: P(continA_B.11|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.896491056 0.002722134 0.045413384 0.098647897
     [1] "fitting the model: P(continA_B.12|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.79057143 -0.04434175 -0.01663036 0.04808361
     [1] "fitting the model: P(continA_B.13|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.70189607 -0.12122423 -0.11539970 0.05274724
     [1] "fitting the model: P(continA_B.14|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.6582717 -0.1360955 -0.1811405 0.1237027
     [1] "fitting the model: P(continA_B.15|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.56509992 -0.04916333 -0.07925828 0.04277256
     [1] "fitting the model: P(continA_B.16|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.51108574 -0.03709401 0.06182217 0.03283527
     [1] "fitting the model: P(continA_B.17|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.351976598 -0.007858614 -0.060311383 -0.064263968
     [1] "fitting the model: P(continA_B.18|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.37937498 0.19296288 0.16413740 0.03544582
     [1] "fitting the model: P(continA_B.19|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.254318960 -0.009143842 0.194735359 0.031597687
     [1] "fitting the model: P(continA_B.20|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.02771289 -0.17474919 -0.02308909 -0.05616704
     [1] "fitting the model: P(continA_B.21|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -2.00520047 -0.22973753 0.18438317 0.08329171
     [1] "fitting the model: P(continA_B.22|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.75157182 0.03163965 0.06238345 -0.10928933
     [1] "fitting the model: P(continA_B.23|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.61911352 -0.13720901 -0.03424895 0.05800888
     [1] "fitting the model: P(continA_B.24|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.36241763 -0.06755052 -0.01618736 -0.02572778
     [1] "fitting the model: P(continA_B.25|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -1.0979427 0.2146947 0.1195034 -0.0981388
     [1] "fitting the model: P(continA_B.26|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -0.75113609 -0.09696295 0.08429001 0.09639133
     [1] "fitting the model: P(continA_B.27|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     -0.0009620808 -0.2764898288 0.0459733993 0.0433252337
     [1] "fitting the model: P(continA_B.28|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     2.656606e+01 4.633733e-06 -9.972023e-08 -2.569638e-08
     [1] "fitting the model: P(continA_B.29|CVD, highA1c, N.tminus1);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept CVD highA1c N.tminus1
     NA NA NA NA
     fit for outcome continA succeeded...
     [1] "fitting the model: P(N|);\\ Stratify: "
     [1] "calling speedglm.wfit..."
     [1] "speedglm fits:"
     Intercept
     -0.01358231
     [1] "performing prediction for continuous outcome: continA"
     [1] "performing prediction for continuous outcome: continA"
     done successfully.
    
     ------------------- UNIT TEST SUMMARY ---------------------
    
     RUNIT TEST PROTOCOL -- Sat Apr 14 10:40:47 2018
     ***********************************************
     Number of test functions: 18
     Number of errors: 1
     Number of failures: 0
    
    
     1 Test Suite :
     stremr unit testing - 18 test functions, 1 error, 0 failures
     ERROR in test.speedglm.allestimators10Kdata: Error in make_report_rmd(OData, NPMSM = list(surv1, surv2), MSM = MSM.IPAW, :
     Failed to compile /tmp/RtmprPfFMF/sim.data.example.fup.tex.
     Error:
    
     unit testing failed (#test failures: 0, #R errors: 1)
    
     Execution halted
Flavor: r-release-linux-x86_64

Version: 0.4
Check: package dependencies
Result: NOTE
    Package suggested but not available for checking: ‘devtools’
Flavor: r-release-osx-x86_64

Version: 0.4
Check: tests
Result: ERROR
     Running ‘test-all.R’ [167s/242s]
    Running the tests in ‘tests/test-all.R’ failed.
    Last 13 lines of output:
     RUNIT TEST PROTOCOL -- Mon Apr 3 00:44:25 2017
     ***********************************************
     Number of test functions: 18
     Number of errors: 1
     Number of failures: 0
    
    
     1 Test Suite :
     stremr unit testing - 18 test functions, 1 error, 0 failures
     ERROR in test.speedglm.allestimators10Kdata: Error in readChar(con, 5L, useBytes = TRUE) : cannot open the connection
     Error:
    
     unit testing failed (#test failures: 0, #R errors: 1)
    
     Execution halted
Flavor: r-release-osx-x86_64