Last updated on 2020-05-29 10:47:22 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.8-4 | 9.65 | 66.87 | 76.52 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 0.8-4 | 7.94 | 51.82 | 59.76 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.8-4 | 105.17 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 0.8-4 | 91.00 | ERROR | |||
| r-devel-windows-ix86+x86_64 | 0.8-4 | 23.00 | 103.00 | 126.00 | ERROR | |
| r-patched-linux-x86_64 | 0.8-4 | 9.34 | 108.28 | 117.62 | OK | |
| r-patched-solaris-x86 | 0.8-4 | 177.70 | OK | |||
| r-release-linux-x86_64 | 0.8-4 | 8.92 | 107.79 | 116.71 | OK | |
| r-release-osx-x86_64 | 0.8-4 | OK | ||||
| r-release-windows-ix86+x86_64 | 0.8-4 | 18.00 | 227.00 | 245.00 | OK | |
| r-oldrel-osx-x86_64 | 0.8-4 | OK | ||||
| r-oldrel-windows-ix86+x86_64 | 0.8-4 | 16.00 | 168.00 | 184.00 | OK |
Version: 0.8-4
Check: examples
Result: ERROR
Running examples in 'gemtc-Ex.R' failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: atrialFibrillation
> ### Title: Prevention of stroke in atrial fibrillation patients
> ### Aliases: atrialFibrillation
>
> ### ** Examples
>
> # Build a model similar to Model 4(b) from Cooper et al. (2009):
> classes <- list("control"=c("01"),
+ "anti-coagulant"=c("02","03","04","09"),
+ "anti-platelet"=c("05","06","07","08","10","11","12","16","17"),
+ "mixed"=c("13","14","15"))
>
> regressor <- list(coefficient='shared',
+ variable='stroke',
+ classes=classes)
>
> model <- mtc.model(atrialFibrillation,
+ type="regression",
+ regressor=regressor,
+ om.scale=10)
Error in x[...] <- m : NAs are not allowed in subscripted assignments
Calls: mtc.model ... %in% -> mtc.network.graph -> comp -> [<- -> [<-.factor
Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Version: 0.8-4
Check: tests
Result: ERROR
Running 'test.R' [13s/14s]
Running the tests in 'tests/test.R' failed.
Complete output:
> library(testthat)
> test_check('gemtc', filter="unit")
Loading required package: gemtc
Loading required package: coda
-- 1. Failure: two pairs return a two-row matrix (@test-unit-allpairs.R#20) ---
`x` not equal to `expected`.
4/4 mismatches (average diff: NaN)
[1] NA - 1.000 == NA
[2] NA - 1.500 == NA
[3] NA - 0.177 == NA
[4] NA - 0.280 == NA
-- 2. Failure: calculating pairs for relative effect data transforms the mvnorm
`x` not equal to `expected`.
4/4 mismatches (average diff: 0.923)
[1] 0 - 0.900 == -0.900
[2] 0 - -1.400 == 1.400
[3] 0 - 0.690 == -0.690
[4] 0 - 0.703 == -0.703
-- 3. Failure: calculating pairs for relative effect data handles 1-pair case (@
`x` not equal to `expected`.
4/4 mismatches (average diff: 0.923)
[1] 0 - 0.900 == -0.900
[2] 0 - -1.400 == 1.400
[3] 0 - 0.690 == -0.690
[4] 0 - 0.703 == -0.703
-- 4. Failure: calculating pairs for relative effect data handles missing treatm
`x` not equal to `expected`.
2/2 mismatches (average diff: 1.05)
[1] 0 - -1.400 == 1.400
[2] 0 - 0.703 == -0.703
-- 5. Failure: guess.scale handles relative effect data (@test-unit-allpairs.R#7
`x` not equal to `expected`.
1/1 mismatches
[1] 0 - 2.3 == -2.3
-- 6. Failure: guess.scale not confused by unrealized study levels (@test-unit-a
`x` not equal to `expected`.
1/1 mismatches
[1] NA - 1.08 == NA
-- 7. Failure: guess.scale not confused by unrealized study levels (@test-unit-a
`x` not equal to `expected`.
1/1 mismatches
[1] 0 - 1 == -1
-- 8. Error: single pair-wise comparison gives FALSE (@test-unit-has.indirect.ev
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 9. Error: comparison in triangle gives TRUE (@test-unit-has.indirect.evidence
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 10. Error: comparison in three-arm trial gives FALSE (@test-unit-has.indirect
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 11. Error: four-arm trials are handled correctly (@test-unit-has.indirect.evi
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 12. Error: data.re is incorporated (@test-unit-has.indirect.evidence.R#101)
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. testthat::expect_that(...)
6. gemtc:::has.indirect.evidence(network, "A", "B")
7. gemtc::mtc.network(data)
8. gemtc:::mtc.network.validate(network)
9. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 13. Error: Vertices agree between mtc.comparisons and the model tree (@test-u
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc::mtc.model(network)
2. gemtc:::mtc.model.call("mtc.model", model, ...)
4. gemtc:::mtc.model.consistency(...)
17. gemtc:::mtc.network.graph(model[["network"]])
18. gemtc:::comp(network)
20. base::`[<-.factor`(...)
-- 14. Error: mtc.comparisons.baseline identical to mtc.comparisons for two-arm
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 15. Error: mtc.comparisons.baseline only includes baseline comparisons for mu
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 16. Error: Vertices agree between mtc.network.graph and ume model$graph (@tes
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::mtc.network.graph(network)
2. gemtc:::comp(network)
4. base::`[<-.factor`(...)
-- 17. Error: RE data will not introduce duplicate basic parameters (@test-unit-
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 18. Error: the model generates correctly (@test-unit-mtc.model.use.R#12) ---
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 19. Error: std.dev + sampleSize is rewritten to std.err (@test-unit-mtc.model
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 20. Error: data.ab missing sampleSize throws error (@test-unit-mtc.model_colu
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 21. Error: data.ab missing std.dev throws error (@test-unit-mtc.model_columns
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 22. Error: data.ab missing mean throws error (@test-unit-mtc.model_columns.R#
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 23. Error: data.ab with std.err does not throw error (@test-unit-mtc.model_co
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 24. Error: mtc.model.data runs on simple data (@test-unit-mtc.model_data.R#8)
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 25. Error: mtc.model.data complains about NAs in data.ab (@test-unit-mtc.mode
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 26. Error: mtc.model.data includes correct fields for data.ab, binom.logit (@
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 27. Error: mtc.model.data includes correct fields for data.ab, binom.cloglog
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 28. Error: mtc.model.data includes correct fields for data.ab, poisson.log (@
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 29. Error: mtc.model.data includes correct fields for data.ab, normal.identit
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 30. Error: mtc.model.data includes correct fields for data.ab, normal.identit
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 31. Error: mtc.model.data includes correct fields for data.ab, binom.logit +
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 32. Error: mtc.model.data omits studies with alpha=0 (powerAdjust) (@test-uni
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re, studies = studies)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 33. Error: mtc.model.data has correct values (1) (@test-unit-mtc.model_data.R
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 34. Error: mtc.model.data has correct values (2) (@test-unit-mtc.model_data.R
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 35. Error: not specifying likelihood / link generates warnings (@test-unit-mt
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_warning(...)
6. gemtc::mtc.model(network, likelihood = "normal")
7. gemtc:::mtc.model.call("mtc.model", model, ...)
9. gemtc:::mtc.model.consistency(...)
22. gemtc:::mtc.network.graph(model[["network"]])
23. gemtc:::comp(network)
25. base::`[<-.factor`(...)
-- 36. Error: mtc.model refuses duplicated arms (@test-unit-mtc.model_duparm.R#4
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(...)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 37. Error: mtc.init.mle.regression just returns 0 +/- om.scale (@test-unit-mt
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 38. Error: mtc.linearModel.matrix works correctly (@test-unit-mtc.model_inits
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 39. Error: mtc.linearModel.matrix works correctly for regression (@test-unit-
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 40. Error: likelihood.arm.list returns the correct arms (@test-unit-mtc.model
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 41. Error: mtc.model.inits has correct shape (@test-unit-mtc.model_inits.R#24
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 42. Error: mtc.model.inits - regression parameters have the correct shape (@t
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, studies = studies)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 43. Error: mtc.model.inits has correct heterogeneity parameter (@test-unit-mt
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 44. Error: mtc.init correctly restrains the baseline probability (@test-unit-
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(read.csv("../data/rr-pairwise.csv"))
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 45. Error: treatments for data.ab and data.re are merged (@test-unit-mtc.netw
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 46. Error: merged list of arms is correct (@test-unit-mtc.network_data.re.R#8
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 47. Error: mtc.nr.comparisons with a single study (@test-unit-mtc.nr.comparis
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 48. Error: mtc.nr.comparisons with 2 studies (@test-unit-mtc.nr.comparisons.R
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 49. Error: mtc.study.treatment.matrix with 1 study (@test-unit-mtc.study.trea
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 50. Error: mtc.study.treatment.matrix with 2 studies (@test-unit-mtc.study.tr
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 51. Error: non-lexicographical treatment order works correctly (@test-unit-no
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, treatments = treatments)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 52. Error: study names do not mess up nodesplit with RE data (@test-unit-node
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_that(...)
6. gemtc::mtc.nodesplit.comparisons(network)
8. gemtc:::mtc.comparisons(network)
10. base::`[<-.factor`(...)
-- 53. Error: mixing AB and RE data will not duplicate comparisons (@test-unit-n
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 54. Error: read.mtc.network('luades-smoking.gemtc') has expected result (@tes
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. testthat::expect_that(read.mtc.network(file), equals(smoking))
6. gemtc::read.mtc.network(file)
7. gemtc::mtc.network(data.ab, treatments = treatments, description = description)
8. gemtc:::mtc.network.validate(network)
9. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 55. Error: read.mtc.network('parkinson.gemtc') has expected result (@test-uni
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. testthat::expect_that(read.mtc.network(file), equals(parkinson))
6. gemtc::read.mtc.network(file)
7. gemtc::mtc.network(data.ab, treatments = treatments, description = description)
8. gemtc:::mtc.network.validate(network)
9. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 56. Error: tree.relative.effect handles a more complex tree (@test-unit-relat
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::minimum.diameter.spanning.tree(mtc.network.graph(network))
8. gemtc:::mtc.network.graph(network)
9. gemtc:::comp(network)
11. base::`[<-.factor`(...)
== testthat results ===========================================================
[ OK: 230 | SKIPPED: 2 | WARNINGS: 0 | FAILED: 56 ]
1. Failure: two pairs return a two-row matrix (@test-unit-allpairs.R#20)
2. Failure: calculating pairs for relative effect data transforms the mvnorm (@test-unit-allpairs.R#33)
3. Failure: calculating pairs for relative effect data handles 1-pair case (@test-unit-allpairs.R#46)
4. Failure: calculating pairs for relative effect data handles missing treatments (@test-unit-allpairs.R#60)
5. Failure: guess.scale handles relative effect data (@test-unit-allpairs.R#76)
6. Failure: guess.scale not confused by unrealized study levels (@test-unit-allpairs.R#82)
7. Failure: guess.scale not confused by unrealized study levels (@test-unit-allpairs.R#86)
8. Error: single pair-wise comparison gives FALSE (@test-unit-has.indirect.evidence.R#7)
9. Error: comparison in triangle gives TRUE (@test-unit-has.indirect.evidence.R#19)
1. ...
Error: testthat unit tests failed
In addition: Warning message:
In extract_lang(f = comp_lang, y = quote(if (.isMethodsDispatchOn() && :
devtools is incompatible with the current version of R. `load_all()` may function incorrectly.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.8-4
Check: tests
Result: ERROR
Running ‘test.R’ [9s/12s]
Running the tests in ‘tests/test.R’ failed.
Complete output:
> library(testthat)
> test_check('gemtc', filter="unit")
Loading required package: gemtc
Loading required package: coda
── 1. Failure: two pairs return a two-row matrix (@test-unit-allpairs.R#20) ───
`x` not equal to `expected`.
4/4 mismatches (average diff: NaN)
[1] NA - 1.000 == NA
[2] NA - 1.500 == NA
[3] NA - 0.177 == NA
[4] NA - 0.280 == NA
── 2. Failure: calculating pairs for relative effect data transforms the mvnorm
`x` not equal to `expected`.
4/4 mismatches (average diff: 0.923)
[1] 0 - 0.900 == -0.900
[2] 0 - -1.400 == 1.400
[3] 0 - 0.690 == -0.690
[4] 0 - 0.703 == -0.703
── 3. Failure: calculating pairs for relative effect data handles 1-pair case (@
`x` not equal to `expected`.
4/4 mismatches (average diff: 0.923)
[1] 0 - 0.900 == -0.900
[2] 0 - -1.400 == 1.400
[3] 0 - 0.690 == -0.690
[4] 0 - 0.703 == -0.703
── 4. Failure: calculating pairs for relative effect data handles missing treatm
`x` not equal to `expected`.
2/2 mismatches (average diff: 1.05)
[1] 0 - -1.400 == 1.400
[2] 0 - 0.703 == -0.703
── 5. Failure: guess.scale handles relative effect data (@test-unit-allpairs.R#7
`x` not equal to `expected`.
1/1 mismatches
[1] 0 - 2.3 == -2.3
── 6. Failure: guess.scale not confused by unrealized study levels (@test-unit-a
`x` not equal to `expected`.
1/1 mismatches
[1] NA - 1.08 == NA
── 7. Failure: guess.scale not confused by unrealized study levels (@test-unit-a
`x` not equal to `expected`.
1/1 mismatches
[1] 0 - 1 == -1
── 8. Error: single pair-wise comparison gives FALSE (@test-unit-has.indirect.ev
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 9. Error: comparison in triangle gives TRUE (@test-unit-has.indirect.evidence
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 10. Error: comparison in three-arm trial gives FALSE (@test-unit-has.indirect
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 11. Error: four-arm trials are handled correctly (@test-unit-has.indirect.evi
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 12. Error: data.re is incorporated (@test-unit-has.indirect.evidence.R#101)
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. testthat::expect_that(...)
6. gemtc:::has.indirect.evidence(network, "A", "B")
7. gemtc::mtc.network(data)
8. gemtc:::mtc.network.validate(network)
9. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 13. Error: Vertices agree between mtc.comparisons and the model tree (@test-u
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc::mtc.model(network)
2. gemtc:::mtc.model.call("mtc.model", model, ...)
4. gemtc:::mtc.model.consistency(...)
17. gemtc:::mtc.network.graph(model[["network"]])
18. gemtc:::comp(network)
20. base::`[<-.factor`(...)
── 14. Error: mtc.comparisons.baseline identical to mtc.comparisons for two-arm
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 15. Error: mtc.comparisons.baseline only includes baseline comparisons for mu
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 16. Error: Vertices agree between mtc.network.graph and ume model$graph (@tes
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::mtc.network.graph(network)
2. gemtc:::comp(network)
4. base::`[<-.factor`(...)
── 17. Error: RE data will not introduce duplicate basic parameters (@test-unit-
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 18. Error: the model generates correctly (@test-unit-mtc.model.use.R#12) ───
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 19. Error: std.dev + sampleSize is rewritten to std.err (@test-unit-mtc.model
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 20. Error: data.ab missing sampleSize throws error (@test-unit-mtc.model_colu
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 21. Error: data.ab missing std.dev throws error (@test-unit-mtc.model_columns
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 22. Error: data.ab missing mean throws error (@test-unit-mtc.model_columns.R#
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 23. Error: data.ab with std.err does not throw error (@test-unit-mtc.model_co
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 24. Error: mtc.model.data runs on simple data (@test-unit-mtc.model_data.R#8)
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 25. Error: mtc.model.data complains about NAs in data.ab (@test-unit-mtc.mode
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 26. Error: mtc.model.data includes correct fields for data.ab, binom.logit (@
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 27. Error: mtc.model.data includes correct fields for data.ab, binom.cloglog
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 28. Error: mtc.model.data includes correct fields for data.ab, poisson.log (@
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 29. Error: mtc.model.data includes correct fields for data.ab, normal.identit
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 30. Error: mtc.model.data includes correct fields for data.ab, normal.identit
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 31. Error: mtc.model.data includes correct fields for data.ab, binom.logit +
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 32. Error: mtc.model.data omits studies with alpha=0 (powerAdjust) (@test-uni
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re, studies = studies)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 33. Error: mtc.model.data has correct values (1) (@test-unit-mtc.model_data.R
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 34. Error: mtc.model.data has correct values (2) (@test-unit-mtc.model_data.R
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 35. Error: not specifying likelihood / link generates warnings (@test-unit-mt
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_warning(...)
6. gemtc::mtc.model(network, likelihood = "normal")
7. gemtc:::mtc.model.call("mtc.model", model, ...)
9. gemtc:::mtc.model.consistency(...)
22. gemtc:::mtc.network.graph(model[["network"]])
23. gemtc:::comp(network)
25. base::`[<-.factor`(...)
── 36. Error: mtc.model refuses duplicated arms (@test-unit-mtc.model_duparm.R#4
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(...)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 37. Error: mtc.init.mle.regression just returns 0 +/- om.scale (@test-unit-mt
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 38. Error: mtc.linearModel.matrix works correctly (@test-unit-mtc.model_inits
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 39. Error: mtc.linearModel.matrix works correctly for regression (@test-unit-
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 40. Error: likelihood.arm.list returns the correct arms (@test-unit-mtc.model
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 41. Error: mtc.model.inits has correct shape (@test-unit-mtc.model_inits.R#24
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 42. Error: mtc.model.inits - regression parameters have the correct shape (@t
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, studies = studies)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 43. Error: mtc.model.inits has correct heterogeneity parameter (@test-unit-mt
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 44. Error: mtc.init correctly restrains the baseline probability (@test-unit-
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(read.csv("../data/rr-pairwise.csv"))
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 45. Error: treatments for data.ab and data.re are merged (@test-unit-mtc.netw
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 46. Error: merged list of arms is correct (@test-unit-mtc.network_data.re.R#8
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 47. Error: mtc.nr.comparisons with a single study (@test-unit-mtc.nr.comparis
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 48. Error: mtc.nr.comparisons with 2 studies (@test-unit-mtc.nr.comparisons.R
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 49. Error: mtc.study.treatment.matrix with 1 study (@test-unit-mtc.study.trea
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 50. Error: mtc.study.treatment.matrix with 2 studies (@test-unit-mtc.study.tr
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 51. Error: non-lexicographical treatment order works correctly (@test-unit-no
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, treatments = treatments)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 52. Error: study names do not mess up nodesplit with RE data (@test-unit-node
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_that(...)
6. gemtc::mtc.nodesplit.comparisons(network)
8. gemtc:::mtc.comparisons(network)
10. base::`[<-.factor`(...)
── 53. Error: mixing AB and RE data will not duplicate comparisons (@test-unit-n
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 54. Error: read.mtc.network('luades-smoking.gemtc') has expected result (@tes
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. testthat::expect_that(read.mtc.network(file), equals(smoking))
6. gemtc::read.mtc.network(file)
7. gemtc::mtc.network(data.ab, treatments = treatments, description = description)
8. gemtc:::mtc.network.validate(network)
9. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 55. Error: read.mtc.network('parkinson.gemtc') has expected result (@test-uni
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. testthat::expect_that(read.mtc.network(file), equals(parkinson))
6. gemtc::read.mtc.network(file)
7. gemtc::mtc.network(data.ab, treatments = treatments, description = description)
8. gemtc:::mtc.network.validate(network)
9. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 56. Error: tree.relative.effect handles a more complex tree (@test-unit-relat
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::minimum.diameter.spanning.tree(mtc.network.graph(network))
8. gemtc:::mtc.network.graph(network)
9. gemtc:::comp(network)
11. base::`[<-.factor`(...)
══ testthat results ═══════════════════════════════════════════════════════════
[ OK: 230 | SKIPPED: 2 | WARNINGS: 0 | FAILED: 56 ]
1. Failure: two pairs return a two-row matrix (@test-unit-allpairs.R#20)
2. Failure: calculating pairs for relative effect data transforms the mvnorm (@test-unit-allpairs.R#33)
3. Failure: calculating pairs for relative effect data handles 1-pair case (@test-unit-allpairs.R#46)
4. Failure: calculating pairs for relative effect data handles missing treatments (@test-unit-allpairs.R#60)
5. Failure: guess.scale handles relative effect data (@test-unit-allpairs.R#76)
6. Failure: guess.scale not confused by unrealized study levels (@test-unit-allpairs.R#82)
7. Failure: guess.scale not confused by unrealized study levels (@test-unit-allpairs.R#86)
8. Error: single pair-wise comparison gives FALSE (@test-unit-has.indirect.evidence.R#7)
9. Error: comparison in triangle gives TRUE (@test-unit-has.indirect.evidence.R#19)
1. ...
Error: testthat unit tests failed
In addition: Warning message:
In extract_lang(f = comp_lang, y = quote(if (.isMethodsDispatchOn() && :
devtools is incompatible with the current version of R. `load_all()` may function incorrectly.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.8-4
Check: examples
Result: ERROR
Running examples in ‘gemtc-Ex.R’ failed
The error most likely occurred in:
> ### Name: atrialFibrillation
> ### Title: Prevention of stroke in atrial fibrillation patients
> ### Aliases: atrialFibrillation
>
> ### ** Examples
>
> # Build a model similar to Model 4(b) from Cooper et al. (2009):
> classes <- list("control"=c("01"),
+ "anti-coagulant"=c("02","03","04","09"),
+ "anti-platelet"=c("05","06","07","08","10","11","12","16","17"),
+ "mixed"=c("13","14","15"))
>
> regressor <- list(coefficient='shared',
+ variable='stroke',
+ classes=classes)
>
> model <- mtc.model(atrialFibrillation,
+ type="regression",
+ regressor=regressor,
+ om.scale=10)
Error in x[...] <- m : NAs are not allowed in subscripted assignments
Calls: mtc.model ... %in% -> mtc.network.graph -> comp -> [<- -> [<-.factor
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 0.8-4
Check: tests
Result: ERROR
Running ‘test.R’ [16s/42s]
Running the tests in ‘tests/test.R’ failed.
Complete output:
> library(testthat)
> test_check('gemtc', filter="unit")
Loading required package: gemtc
Loading required package: coda
── 1. Failure: two pairs return a two-row matrix (@test-unit-allpairs.R#20) ───
`x` not equal to `expected`.
4/4 mismatches (average diff: NaN)
[1] NA - 1.000 == NA
[2] NA - 1.500 == NA
[3] NA - 0.177 == NA
[4] NA - 0.280 == NA
── 2. Failure: calculating pairs for relative effect data transforms the mvnorm
`x` not equal to `expected`.
4/4 mismatches (average diff: 0.923)
[1] 0 - 0.900 == -0.900
[2] 0 - -1.400 == 1.400
[3] 0 - 0.690 == -0.690
[4] 0 - 0.703 == -0.703
── 3. Failure: calculating pairs for relative effect data handles 1-pair case (@
`x` not equal to `expected`.
4/4 mismatches (average diff: 0.923)
[1] 0 - 0.900 == -0.900
[2] 0 - -1.400 == 1.400
[3] 0 - 0.690 == -0.690
[4] 0 - 0.703 == -0.703
── 4. Failure: calculating pairs for relative effect data handles missing treatm
`x` not equal to `expected`.
2/2 mismatches (average diff: 1.05)
[1] 0 - -1.400 == 1.400
[2] 0 - 0.703 == -0.703
── 5. Failure: guess.scale handles relative effect data (@test-unit-allpairs.R#7
`x` not equal to `expected`.
1/1 mismatches
[1] 0 - 2.3 == -2.3
── 6. Failure: guess.scale not confused by unrealized study levels (@test-unit-a
`x` not equal to `expected`.
1/1 mismatches
[1] NA - 1.08 == NA
── 7. Failure: guess.scale not confused by unrealized study levels (@test-unit-a
`x` not equal to `expected`.
1/1 mismatches
[1] 0 - 1 == -1
── 8. Error: comparison in triangle gives TRUE (@test-unit-has.indirect.evidence
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_that(...)
6. gemtc:::has.indirect.evidence(network, "A", "B")
7. gemtc:::mtc.network.graph(n)
8. gemtc:::comp(network)
10. base::`[<-.factor`(...)
── 9. Error: comparison in three-arm trial gives FALSE (@test-unit-has.indirect.
Invalid vertex names
Backtrace:
1. testthat::expect_that(...)
6. gemtc:::has.indirect.evidence(network, "A", "B")
7. gemtc:::mtc.network.graph(n)
8. gemtc:::graph.create(treatments, comparisons, arrow.mode = 0)
9. igraph:::`+.igraph`(g, edges.create(e, ...))
12. igraph:::as.igraph.vs(e1, toadd)
── 10. Error: four-arm trials are handled correctly (@test-unit-has.indirect.evi
Invalid vertex names
Backtrace:
1. testthat::expect_that(...)
6. gemtc:::has.indirect.evidence(network, "A", "B")
7. gemtc:::mtc.network.graph(n)
8. gemtc:::graph.create(treatments, comparisons, arrow.mode = 0)
9. igraph:::`+.igraph`(g, edges.create(e, ...))
12. igraph:::as.igraph.vs(e1, toadd)
── 11. Error: data.re is incorporated (@test-unit-has.indirect.evidence.R#101)
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_that(...)
6. gemtc:::has.indirect.evidence(network, "A", "B")
7. gemtc:::mtc.network.graph(n)
8. gemtc:::comp(network)
10. base::`[<-.factor`(...)
── 12. Error: Vertices agree between mtc.comparisons and the model tree (@test-u
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc::mtc.model(network)
2. gemtc:::mtc.model.call("mtc.model", model, ...)
4. gemtc:::mtc.model.consistency(...)
17. gemtc:::mtc.network.graph(model[["network"]])
18. gemtc:::comp(network)
20. base::`[<-.factor`(...)
── 13. Error: mtc.comparisons.baseline identical to mtc.comparisons for two-arm
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_that(mtc.comparisons.baseline(network), equals(mtc.comparisons(network)))
6. gemtc:::mtc.comparisons(network)
8. base::`[<-.factor`(...)
── 14. Error: Vertices agree between mtc.network.graph and ume model$graph (@tes
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::mtc.network.graph(network)
2. gemtc:::comp(network)
4. base::`[<-.factor`(...)
── 15. Error: RE data will not introduce duplicate basic parameters (@test-unit-
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 16. Error: std.dev + sampleSize is rewritten to std.err (@test-unit-mtc.model
Invalid vertex names
Backtrace:
1. gemtc::mtc.model(network, likelihood = "normal", link = "identity")
2. gemtc:::mtc.model.call("mtc.model", model, ...)
4. gemtc:::mtc.model.consistency(...)
17. gemtc:::mtc.network.graph(model[["network"]])
18. gemtc:::graph.create(treatments, comparisons, arrow.mode = 0)
19. igraph:::`+.igraph`(g, edges.create(e, ...))
22. igraph:::as.igraph.vs(e1, toadd)
── 17. Error: data.ab with std.err does not throw error (@test-unit-mtc.model_co
Invalid vertex names
Backtrace:
1. gemtc::mtc.model(network, likelihood = "normal", link = "identity")
2. gemtc:::mtc.model.call("mtc.model", model, ...)
4. gemtc:::mtc.model.consistency(...)
17. gemtc:::mtc.network.graph(model[["network"]])
18. gemtc:::graph.create(treatments, comparisons, arrow.mode = 0)
19. igraph:::`+.igraph`(g, edges.create(e, ...))
22. igraph:::as.igraph.vs(e1, toadd)
── 18. Error: mtc.model.data includes correct fields for data.ab, normal.identit
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 19. Error: mtc.model.data includes correct fields for data.ab, binom.logit +
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 20. Error: mtc.model.data omits studies with alpha=0 (powerAdjust) (@test-uni
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re, studies = studies)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 21. Error: mtc.model.data has correct values (1) (@test-unit-mtc.model_data.R
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 22. Error: mtc.model.data has correct values (2) (@test-unit-mtc.model_data.R
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 23. Error: not specifying likelihood / link generates warnings (@test-unit-mt
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_warning(...)
6. gemtc::mtc.model(network, likelihood = "normal")
7. gemtc:::mtc.model.call("mtc.model", model, ...)
9. gemtc:::mtc.model.consistency(...)
22. gemtc:::mtc.network.graph(model[["network"]])
23. gemtc:::comp(network)
25. base::`[<-.factor`(...)
── 24. Error: mtc.init.mle.regression just returns 0 +/- om.scale (@test-unit-mt
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::minimum.diameter.spanning.tree(mtc.network.graph(network))
8. gemtc:::mtc.network.graph(network)
9. gemtc:::comp(network)
11. base::`[<-.factor`(...)
── 25. Error: mtc.linearModel.matrix works correctly (@test-unit-mtc.model_inits
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 26. Error: mtc.linearModel.matrix works correctly for regression (@test-unit-
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 27. Error: likelihood.arm.list returns the correct arms (@test-unit-mtc.model
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 28. Error: mtc.model.inits has correct shape (@test-unit-mtc.model_inits.R#24
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 29. Error: mtc.model.inits - regression parameters have the correct shape (@t
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::minimum.diameter.spanning.tree(mtc.network.graph(network))
8. gemtc:::mtc.network.graph(network)
9. gemtc:::comp(network)
11. base::`[<-.factor`(...)
── 30. Error: mtc.model.inits has correct heterogeneity parameter (@test-unit-mt
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::minimum.diameter.spanning.tree(mtc.network.graph(network))
8. gemtc:::mtc.network.graph(network)
9. gemtc:::comp(network)
11. base::`[<-.factor`(...)
── 31. Error: mtc.init correctly restrains the baseline probability (@test-unit-
Invalid vertex names
Backtrace:
1. gemtc:::minimum.diameter.spanning.tree(mtc.network.graph(network))
8. gemtc:::mtc.network.graph(network)
9. gemtc:::graph.create(treatments, comparisons, arrow.mode = 0)
10. igraph:::`+.igraph`(g, edges.create(e, ...))
13. igraph:::as.igraph.vs(e1, toadd)
── 32. Error: treatments for data.ab and data.re are merged (@test-unit-mtc.netw
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 33. Error: merged list of arms is correct (@test-unit-mtc.network_data.re.R#8
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 34. Error: mtc.nr.comparisons with a single study (@test-unit-mtc.nr.comparis
subscript out of bounds
Backtrace:
1. gemtc:::mtc.nr.comparisons(network)
2. plyr::aaply(...)
3. plyr::laply(...)
4. plyr::llply(...)
7. gemtc:::.fun(piece, ...)
8. base::rowSums(m[, co, drop = FALSE])
9. base::is.data.frame(x)
── 35. Error: mtc.nr.comparisons with 2 studies (@test-unit-mtc.nr.comparisons.R
subscript out of bounds
Backtrace:
1. gemtc:::mtc.nr.comparisons(network)
2. plyr::aaply(...)
3. plyr::laply(...)
4. plyr::llply(...)
7. gemtc:::.fun(piece, ...)
8. base::rowSums(m[, co, drop = FALSE])
9. base::is.data.frame(x)
── 36. Error: non-lexicographical treatment order works correctly (@test-unit-no
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc::mtc.model(network, type = "nodesplit", t1 = 10, t2 = 11)
2. gemtc:::mtc.model.call("mtc.model", model, ...)
4. gemtc:::mtc.model.nodesplit(...)
6. gemtc:::has.indirect.evidence(network, t1, t2)
7. gemtc:::mtc.network.graph(n)
8. gemtc:::comp(network)
10. base::`[<-.factor`(...)
── 37. Error: study names do not mess up nodesplit with RE data (@test-unit-node
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_that(...)
6. gemtc::mtc.nodesplit.comparisons(network)
8. gemtc:::mtc.comparisons(network)
10. base::`[<-.factor`(...)
── 38. Error: mixing AB and RE data will not duplicate comparisons (@test-unit-n
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 39. Error: tree.relative.effect handles a more complex tree (@test-unit-relat
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::minimum.diameter.spanning.tree(mtc.network.graph(network))
8. gemtc:::mtc.network.graph(network)
9. gemtc:::comp(network)
11. base::`[<-.factor`(...)
══ testthat results ═══════════════════════════════════════════════════════════
[ OK: 256 | SKIPPED: 2 | WARNINGS: 1 | FAILED: 39 ]
1. Failure: two pairs return a two-row matrix (@test-unit-allpairs.R#20)
2. Failure: calculating pairs for relative effect data transforms the mvnorm (@test-unit-allpairs.R#33)
3. Failure: calculating pairs for relative effect data handles 1-pair case (@test-unit-allpairs.R#46)
4. Failure: calculating pairs for relative effect data handles missing treatments (@test-unit-allpairs.R#60)
5. Failure: guess.scale handles relative effect data (@test-unit-allpairs.R#76)
6. Failure: guess.scale not confused by unrealized study levels (@test-unit-allpairs.R#82)
7. Failure: guess.scale not confused by unrealized study levels (@test-unit-allpairs.R#86)
8. Error: comparison in triangle gives TRUE (@test-unit-has.indirect.evidence.R#20)
9. Error: comparison in three-arm trial gives FALSE (@test-unit-has.indirect.evidence.R#49)
1. ...
Error: testthat unit tests failed
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.8-4
Check: tests
Result: ERROR
Running ‘test.R’ [15s/18s]
Running the tests in ‘tests/test.R’ failed.
Complete output:
> library(testthat)
> test_check('gemtc', filter="unit")
Loading required package: gemtc
Loading required package: coda
── 1. Failure: two pairs return a two-row matrix (@test-unit-allpairs.R#20) ───
`x` not equal to `expected`.
4/4 mismatches (average diff: NaN)
[1] NA - 1.000 == NA
[2] NA - 1.500 == NA
[3] NA - 0.177 == NA
[4] NA - 0.280 == NA
── 2. Failure: calculating pairs for relative effect data transforms the mvnorm
`x` not equal to `expected`.
4/4 mismatches (average diff: 0.923)
[1] 0 - 0.900 == -0.900
[2] 0 - -1.400 == 1.400
[3] 0 - 0.690 == -0.690
[4] 0 - 0.703 == -0.703
── 3. Failure: calculating pairs for relative effect data handles 1-pair case (@
`x` not equal to `expected`.
4/4 mismatches (average diff: 0.923)
[1] 0 - 0.900 == -0.900
[2] 0 - -1.400 == 1.400
[3] 0 - 0.690 == -0.690
[4] 0 - 0.703 == -0.703
── 4. Failure: calculating pairs for relative effect data handles missing treatm
`x` not equal to `expected`.
2/2 mismatches (average diff: 1.05)
[1] 0 - -1.400 == 1.400
[2] 0 - 0.703 == -0.703
── 5. Failure: guess.scale handles relative effect data (@test-unit-allpairs.R#7
`x` not equal to `expected`.
1/1 mismatches
[1] 0 - 2.3 == -2.3
── 6. Failure: guess.scale not confused by unrealized study levels (@test-unit-a
`x` not equal to `expected`.
1/1 mismatches
[1] NA - 1.08 == NA
── 7. Failure: guess.scale not confused by unrealized study levels (@test-unit-a
`x` not equal to `expected`.
1/1 mismatches
[1] 0 - 1 == -1
── 8. Error: comparison in triangle gives TRUE (@test-unit-has.indirect.evidence
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_that(...)
6. gemtc:::has.indirect.evidence(network, "A", "B")
7. gemtc:::mtc.network.graph(n)
8. gemtc:::comp(network)
10. base::`[<-.factor`(...)
── 9. Error: comparison in three-arm trial gives FALSE (@test-unit-has.indirect.
Invalid vertex names
Backtrace:
1. testthat::expect_that(...)
6. gemtc:::has.indirect.evidence(network, "A", "B")
7. gemtc:::mtc.network.graph(n)
8. gemtc:::graph.create(treatments, comparisons, arrow.mode = 0)
9. igraph:::`+.igraph`(g, edges.create(e, ...))
12. igraph:::as.igraph.vs(e1, toadd)
── 10. Error: four-arm trials are handled correctly (@test-unit-has.indirect.evi
Invalid vertex names
Backtrace:
1. testthat::expect_that(...)
6. gemtc:::has.indirect.evidence(network, "A", "B")
7. gemtc:::mtc.network.graph(n)
8. gemtc:::graph.create(treatments, comparisons, arrow.mode = 0)
9. igraph:::`+.igraph`(g, edges.create(e, ...))
12. igraph:::as.igraph.vs(e1, toadd)
── 11. Error: data.re is incorporated (@test-unit-has.indirect.evidence.R#101)
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_that(...)
6. gemtc:::has.indirect.evidence(network, "A", "B")
7. gemtc:::mtc.network.graph(n)
8. gemtc:::comp(network)
10. base::`[<-.factor`(...)
── 12. Error: Vertices agree between mtc.comparisons and the model tree (@test-u
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc::mtc.model(network)
2. gemtc:::mtc.model.call("mtc.model", model, ...)
4. gemtc:::mtc.model.consistency(...)
17. gemtc:::mtc.network.graph(model[["network"]])
18. gemtc:::comp(network)
20. base::`[<-.factor`(...)
── 13. Error: mtc.comparisons.baseline identical to mtc.comparisons for two-arm
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_that(mtc.comparisons.baseline(network), equals(mtc.comparisons(network)))
6. gemtc:::mtc.comparisons(network)
8. base::`[<-.factor`(...)
── 14. Error: Vertices agree between mtc.network.graph and ume model$graph (@tes
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::mtc.network.graph(network)
2. gemtc:::comp(network)
4. base::`[<-.factor`(...)
── 15. Error: RE data will not introduce duplicate basic parameters (@test-unit-
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 16. Error: std.dev + sampleSize is rewritten to std.err (@test-unit-mtc.model
Invalid vertex names
Backtrace:
1. gemtc::mtc.model(network, likelihood = "normal", link = "identity")
2. gemtc:::mtc.model.call("mtc.model", model, ...)
4. gemtc:::mtc.model.consistency(...)
17. gemtc:::mtc.network.graph(model[["network"]])
18. gemtc:::graph.create(treatments, comparisons, arrow.mode = 0)
19. igraph:::`+.igraph`(g, edges.create(e, ...))
22. igraph:::as.igraph.vs(e1, toadd)
── 17. Error: data.ab with std.err does not throw error (@test-unit-mtc.model_co
Invalid vertex names
Backtrace:
1. gemtc::mtc.model(network, likelihood = "normal", link = "identity")
2. gemtc:::mtc.model.call("mtc.model", model, ...)
4. gemtc:::mtc.model.consistency(...)
17. gemtc:::mtc.network.graph(model[["network"]])
18. gemtc:::graph.create(treatments, comparisons, arrow.mode = 0)
19. igraph:::`+.igraph`(g, edges.create(e, ...))
22. igraph:::as.igraph.vs(e1, toadd)
── 18. Error: mtc.model.data includes correct fields for data.ab, normal.identit
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 19. Error: mtc.model.data includes correct fields for data.ab, binom.logit +
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 20. Error: mtc.model.data omits studies with alpha=0 (powerAdjust) (@test-uni
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re, studies = studies)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 21. Error: mtc.model.data has correct values (1) (@test-unit-mtc.model_data.R
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 22. Error: mtc.model.data has correct values (2) (@test-unit-mtc.model_data.R
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 23. Error: not specifying likelihood / link generates warnings (@test-unit-mt
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_warning(...)
6. gemtc::mtc.model(network, likelihood = "normal")
7. gemtc:::mtc.model.call("mtc.model", model, ...)
9. gemtc:::mtc.model.consistency(...)
22. gemtc:::mtc.network.graph(model[["network"]])
23. gemtc:::comp(network)
25. base::`[<-.factor`(...)
── 24. Error: mtc.init.mle.regression just returns 0 +/- om.scale (@test-unit-mt
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::minimum.diameter.spanning.tree(mtc.network.graph(network))
8. gemtc:::mtc.network.graph(network)
9. gemtc:::comp(network)
11. base::`[<-.factor`(...)
── 25. Error: mtc.linearModel.matrix works correctly (@test-unit-mtc.model_inits
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 26. Error: mtc.linearModel.matrix works correctly for regression (@test-unit-
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 27. Error: likelihood.arm.list returns the correct arms (@test-unit-mtc.model
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 28. Error: mtc.model.inits has correct shape (@test-unit-mtc.model_inits.R#24
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 29. Error: mtc.model.inits - regression parameters have the correct shape (@t
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::minimum.diameter.spanning.tree(mtc.network.graph(network))
8. gemtc:::mtc.network.graph(network)
9. gemtc:::comp(network)
11. base::`[<-.factor`(...)
── 30. Error: mtc.model.inits has correct heterogeneity parameter (@test-unit-mt
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::minimum.diameter.spanning.tree(mtc.network.graph(network))
8. gemtc:::mtc.network.graph(network)
9. gemtc:::comp(network)
11. base::`[<-.factor`(...)
── 31. Error: mtc.init correctly restrains the baseline probability (@test-unit-
Invalid vertex names
Backtrace:
1. gemtc:::minimum.diameter.spanning.tree(mtc.network.graph(network))
8. gemtc:::mtc.network.graph(network)
9. gemtc:::graph.create(treatments, comparisons, arrow.mode = 0)
10. igraph:::`+.igraph`(g, edges.create(e, ...))
13. igraph:::as.igraph.vs(e1, toadd)
── 32. Error: treatments for data.ab and data.re are merged (@test-unit-mtc.netw
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 33. Error: merged list of arms is correct (@test-unit-mtc.network_data.re.R#8
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 34. Error: mtc.nr.comparisons with a single study (@test-unit-mtc.nr.comparis
subscript out of bounds
Backtrace:
1. gemtc:::mtc.nr.comparisons(network)
2. plyr::aaply(...)
3. plyr::laply(...)
4. plyr::llply(...)
7. gemtc:::.fun(piece, ...)
8. base::rowSums(m[, co, drop = FALSE])
9. base::is.data.frame(x)
── 35. Error: mtc.nr.comparisons with 2 studies (@test-unit-mtc.nr.comparisons.R
subscript out of bounds
Backtrace:
1. gemtc:::mtc.nr.comparisons(network)
2. plyr::aaply(...)
3. plyr::laply(...)
4. plyr::llply(...)
7. gemtc:::.fun(piece, ...)
8. base::rowSums(m[, co, drop = FALSE])
9. base::is.data.frame(x)
── 36. Error: non-lexicographical treatment order works correctly (@test-unit-no
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc::mtc.model(network, type = "nodesplit", t1 = 10, t2 = 11)
2. gemtc:::mtc.model.call("mtc.model", model, ...)
4. gemtc:::mtc.model.nodesplit(...)
6. gemtc:::has.indirect.evidence(network, t1, t2)
7. gemtc:::mtc.network.graph(n)
8. gemtc:::comp(network)
10. base::`[<-.factor`(...)
── 37. Error: study names do not mess up nodesplit with RE data (@test-unit-node
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_that(...)
6. gemtc::mtc.nodesplit.comparisons(network)
8. gemtc:::mtc.comparisons(network)
10. base::`[<-.factor`(...)
── 38. Error: mixing AB and RE data will not duplicate comparisons (@test-unit-n
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
── 39. Error: tree.relative.effect handles a more complex tree (@test-unit-relat
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::minimum.diameter.spanning.tree(mtc.network.graph(network))
8. gemtc:::mtc.network.graph(network)
9. gemtc:::comp(network)
11. base::`[<-.factor`(...)
══ testthat results ═══════════════════════════════════════════════════════════
[ OK: 256 | SKIPPED: 2 | WARNINGS: 1 | FAILED: 39 ]
1. Failure: two pairs return a two-row matrix (@test-unit-allpairs.R#20)
2. Failure: calculating pairs for relative effect data transforms the mvnorm (@test-unit-allpairs.R#33)
3. Failure: calculating pairs for relative effect data handles 1-pair case (@test-unit-allpairs.R#46)
4. Failure: calculating pairs for relative effect data handles missing treatments (@test-unit-allpairs.R#60)
5. Failure: guess.scale handles relative effect data (@test-unit-allpairs.R#76)
6. Failure: guess.scale not confused by unrealized study levels (@test-unit-allpairs.R#82)
7. Failure: guess.scale not confused by unrealized study levels (@test-unit-allpairs.R#86)
8. Error: comparison in triangle gives TRUE (@test-unit-has.indirect.evidence.R#20)
9. Error: comparison in three-arm trial gives FALSE (@test-unit-has.indirect.evidence.R#49)
1. ...
Error: testthat unit tests failed
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.8-4
Check: running examples for arch ‘i386’
Result: ERROR
Running examples in 'gemtc-Ex.R' failed
The error most likely occurred in:
> ### Name: atrialFibrillation
> ### Title: Prevention of stroke in atrial fibrillation patients
> ### Aliases: atrialFibrillation
>
> ### ** Examples
>
> # Build a model similar to Model 4(b) from Cooper et al. (2009):
> classes <- list("control"=c("01"),
+ "anti-coagulant"=c("02","03","04","09"),
+ "anti-platelet"=c("05","06","07","08","10","11","12","16","17"),
+ "mixed"=c("13","14","15"))
>
> regressor <- list(coefficient='shared',
+ variable='stroke',
+ classes=classes)
>
> model <- mtc.model(atrialFibrillation,
+ type="regression",
+ regressor=regressor,
+ om.scale=10)
Error in x[...] <- m : NAs are not allowed in subscripted assignments
Calls: mtc.model ... %in% -> mtc.network.graph -> comp -> [<- -> [<-.factor
Execution halted
Flavor: r-devel-windows-ix86+x86_64
Version: 0.8-4
Check: running examples for arch ‘x64’
Result: ERROR
Running examples in 'gemtc-Ex.R' failed
The error most likely occurred in:
> ### Name: atrialFibrillation
> ### Title: Prevention of stroke in atrial fibrillation patients
> ### Aliases: atrialFibrillation
>
> ### ** Examples
>
> # Build a model similar to Model 4(b) from Cooper et al. (2009):
> classes <- list("control"=c("01"),
+ "anti-coagulant"=c("02","03","04","09"),
+ "anti-platelet"=c("05","06","07","08","10","11","12","16","17"),
+ "mixed"=c("13","14","15"))
>
> regressor <- list(coefficient='shared',
+ variable='stroke',
+ classes=classes)
>
> model <- mtc.model(atrialFibrillation,
+ type="regression",
+ regressor=regressor,
+ om.scale=10)
Error in x[...] <- m : NAs are not allowed in subscripted assignments
Calls: mtc.model ... %in% -> mtc.network.graph -> comp -> [<- -> [<-.factor
Execution halted
Flavor: r-devel-windows-ix86+x86_64
Version: 0.8-4
Check: running tests for arch ‘i386’
Result: ERROR
Running 'test.R' [11s]
Running the tests in 'tests/test.R' failed.
Complete output:
> library(testthat)
> test_check('gemtc', filter="unit")
Loading required package: gemtc
Loading required package: coda
-- 1. Failure: two pairs return a two-row matrix (@test-unit-allpairs.R#20) ---
`x` not equal to `expected`.
4/4 mismatches (average diff: NaN)
[1] NA - 1.000 == NA
[2] NA - 1.500 == NA
[3] NA - 0.177 == NA
[4] NA - 0.280 == NA
-- 2. Failure: calculating pairs for relative effect data transforms the mvnorm
`x` not equal to `expected`.
4/4 mismatches (average diff: 0.923)
[1] 0 - 0.900 == -0.900
[2] 0 - -1.400 == 1.400
[3] 0 - 0.690 == -0.690
[4] 0 - 0.703 == -0.703
-- 3. Failure: calculating pairs for relative effect data handles 1-pair case (@
`x` not equal to `expected`.
4/4 mismatches (average diff: 0.923)
[1] 0 - 0.900 == -0.900
[2] 0 - -1.400 == 1.400
[3] 0 - 0.690 == -0.690
[4] 0 - 0.703 == -0.703
-- 4. Failure: calculating pairs for relative effect data handles missing treatm
`x` not equal to `expected`.
2/2 mismatches (average diff: 1.05)
[1] 0 - -1.400 == 1.400
[2] 0 - 0.703 == -0.703
-- 5. Failure: guess.scale handles relative effect data (@test-unit-allpairs.R#7
`x` not equal to `expected`.
1/1 mismatches
[1] 0 - 2.3 == -2.3
-- 6. Failure: guess.scale not confused by unrealized study levels (@test-unit-a
`x` not equal to `expected`.
1/1 mismatches
[1] NA - 1.08 == NA
-- 7. Failure: guess.scale not confused by unrealized study levels (@test-unit-a
`x` not equal to `expected`.
1/1 mismatches
[1] 0 - 1 == -1
-- 8. Error: single pair-wise comparison gives FALSE (@test-unit-has.indirect.ev
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 9. Error: comparison in triangle gives TRUE (@test-unit-has.indirect.evidence
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 10. Error: comparison in three-arm trial gives FALSE (@test-unit-has.indirect
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 11. Error: four-arm trials are handled correctly (@test-unit-has.indirect.evi
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 12. Error: data.re is incorporated (@test-unit-has.indirect.evidence.R#101)
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. testthat::expect_that(...)
6. gemtc:::has.indirect.evidence(network, "A", "B")
7. gemtc::mtc.network(data)
8. gemtc:::mtc.network.validate(network)
9. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 13. Error: Vertices agree between mtc.comparisons and the model tree (@test-u
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc::mtc.model(network)
2. gemtc:::mtc.model.call("mtc.model", model, ...)
4. gemtc:::mtc.model.consistency(...)
17. gemtc:::mtc.network.graph(model[["network"]])
18. gemtc:::comp(network)
20. base::`[<-.factor`(...)
-- 14. Error: mtc.comparisons.baseline identical to mtc.comparisons for two-arm
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 15. Error: mtc.comparisons.baseline only includes baseline comparisons for mu
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 16. Error: Vertices agree between mtc.network.graph and ume model$graph (@tes
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::mtc.network.graph(network)
2. gemtc:::comp(network)
4. base::`[<-.factor`(...)
-- 17. Error: RE data will not introduce duplicate basic parameters (@test-unit-
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 18. Error: the model generates correctly (@test-unit-mtc.model.use.R#12) ---
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 19. Error: std.dev + sampleSize is rewritten to std.err (@test-unit-mtc.model
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 20. Error: data.ab missing sampleSize throws error (@test-unit-mtc.model_colu
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 21. Error: data.ab missing std.dev throws error (@test-unit-mtc.model_columns
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 22. Error: data.ab missing mean throws error (@test-unit-mtc.model_columns.R#
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 23. Error: data.ab with std.err does not throw error (@test-unit-mtc.model_co
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 24. Error: mtc.model.data runs on simple data (@test-unit-mtc.model_data.R#8)
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 25. Error: mtc.model.data complains about NAs in data.ab (@test-unit-mtc.mode
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 26. Error: mtc.model.data includes correct fields for data.ab, binom.logit (@
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 27. Error: mtc.model.data includes correct fields for data.ab, binom.cloglog
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 28. Error: mtc.model.data includes correct fields for data.ab, poisson.log (@
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 29. Error: mtc.model.data includes correct fields for data.ab, normal.identit
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 30. Error: mtc.model.data includes correct fields for data.ab, normal.identit
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 31. Error: mtc.model.data includes correct fields for data.ab, binom.logit +
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 32. Error: mtc.model.data omits studies with alpha=0 (powerAdjust) (@test-uni
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re, studies = studies)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 33. Error: mtc.model.data has correct values (1) (@test-unit-mtc.model_data.R
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 34. Error: mtc.model.data has correct values (2) (@test-unit-mtc.model_data.R
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 35. Error: not specifying likelihood / link generates warnings (@test-unit-mt
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_warning(...)
6. gemtc::mtc.model(network, likelihood = "normal")
7. gemtc:::mtc.model.call("mtc.model", model, ...)
9. gemtc:::mtc.model.consistency(...)
22. gemtc:::mtc.network.graph(model[["network"]])
23. gemtc:::comp(network)
25. base::`[<-.factor`(...)
-- 36. Error: mtc.model refuses duplicated arms (@test-unit-mtc.model_duparm.R#4
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(...)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 37. Error: mtc.init.mle.regression just returns 0 +/- om.scale (@test-unit-mt
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 38. Error: mtc.linearModel.matrix works correctly (@test-unit-mtc.model_inits
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 39. Error: mtc.linearModel.matrix works correctly for regression (@test-unit-
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 40. Error: likelihood.arm.list returns the correct arms (@test-unit-mtc.model
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 41. Error: mtc.model.inits has correct shape (@test-unit-mtc.model_inits.R#24
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 42. Error: mtc.model.inits - regression parameters have the correct shape (@t
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, studies = studies)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 43. Error: mtc.model.inits has correct heterogeneity parameter (@test-unit-mt
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 44. Error: mtc.init correctly restrains the baseline probability (@test-unit-
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(read.csv("../data/rr-pairwise.csv"))
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 45. Error: treatments for data.ab and data.re are merged (@test-unit-mtc.netw
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 46. Error: merged list of arms is correct (@test-unit-mtc.network_data.re.R#8
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 47. Error: mtc.nr.comparisons with a single study (@test-unit-mtc.nr.comparis
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 48. Error: mtc.nr.comparisons with 2 studies (@test-unit-mtc.nr.comparisons.R
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 49. Error: mtc.study.treatment.matrix with 1 study (@test-unit-mtc.study.trea
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 50. Error: mtc.study.treatment.matrix with 2 studies (@test-unit-mtc.study.tr
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 51. Error: non-lexicographical treatment order works correctly (@test-unit-no
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, treatments = treatments)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 52. Error: study names do not mess up nodesplit with RE data (@test-unit-node
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_that(...)
6. gemtc::mtc.nodesplit.comparisons(network)
8. gemtc:::mtc.comparisons(network)
10. base::`[<-.factor`(...)
-- 53. Error: mixing AB and RE data will not duplicate comparisons (@test-unit-n
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 54. Error: read.mtc.network('luades-smoking.gemtc') has expected result (@tes
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. testthat::expect_that(read.mtc.network(file), equals(smoking))
6. gemtc::read.mtc.network(file)
7. gemtc::mtc.network(data.ab, treatments = treatments, description = description)
8. gemtc:::mtc.network.validate(network)
9. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 55. Error: read.mtc.network('parkinson.gemtc') has expected result (@test-uni
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. testthat::expect_that(read.mtc.network(file), equals(parkinson))
6. gemtc::read.mtc.network(file)
7. gemtc::mtc.network(data.ab, treatments = treatments, description = description)
8. gemtc:::mtc.network.validate(network)
9. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 56. Error: tree.relative.effect handles a more complex tree (@test-unit-relat
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::minimum.diameter.spanning.tree(mtc.network.graph(network))
8. gemtc:::mtc.network.graph(network)
9. gemtc:::comp(network)
11. base::`[<-.factor`(...)
== testthat results ===========================================================
[ OK: 230 | SKIPPED: 2 | WARNINGS: 0 | FAILED: 56 ]
1. Failure: two pairs return a two-row matrix (@test-unit-allpairs.R#20)
2. Failure: calculating pairs for relative effect data transforms the mvnorm (@test-unit-allpairs.R#33)
3. Failure: calculating pairs for relative effect data handles 1-pair case (@test-unit-allpairs.R#46)
4. Failure: calculating pairs for relative effect data handles missing treatments (@test-unit-allpairs.R#60)
5. Failure: guess.scale handles relative effect data (@test-unit-allpairs.R#76)
6. Failure: guess.scale not confused by unrealized study levels (@test-unit-allpairs.R#82)
7. Failure: guess.scale not confused by unrealized study levels (@test-unit-allpairs.R#86)
8. Error: single pair-wise comparison gives FALSE (@test-unit-has.indirect.evidence.R#7)
9. Error: comparison in triangle gives TRUE (@test-unit-has.indirect.evidence.R#19)
1. ...
Error: testthat unit tests failed
In addition: Warning message:
In extract_lang(f = comp_lang, y = quote(if (.isMethodsDispatchOn() && :
devtools is incompatible with the current version of R. `load_all()` may function incorrectly.
Execution halted
Flavor: r-devel-windows-ix86+x86_64
Version: 0.8-4
Check: running tests for arch ‘x64’
Result: ERROR
Running 'test.R' [12s]
Running the tests in 'tests/test.R' failed.
Complete output:
> library(testthat)
> test_check('gemtc', filter="unit")
Loading required package: gemtc
Loading required package: coda
-- 1. Failure: two pairs return a two-row matrix (@test-unit-allpairs.R#20) ---
`x` not equal to `expected`.
4/4 mismatches (average diff: NaN)
[1] NA - 1.000 == NA
[2] NA - 1.500 == NA
[3] NA - 0.177 == NA
[4] NA - 0.280 == NA
-- 2. Failure: calculating pairs for relative effect data transforms the mvnorm
`x` not equal to `expected`.
4/4 mismatches (average diff: 0.923)
[1] 0 - 0.900 == -0.900
[2] 0 - -1.400 == 1.400
[3] 0 - 0.690 == -0.690
[4] 0 - 0.703 == -0.703
-- 3. Failure: calculating pairs for relative effect data handles 1-pair case (@
`x` not equal to `expected`.
4/4 mismatches (average diff: 0.923)
[1] 0 - 0.900 == -0.900
[2] 0 - -1.400 == 1.400
[3] 0 - 0.690 == -0.690
[4] 0 - 0.703 == -0.703
-- 4. Failure: calculating pairs for relative effect data handles missing treatm
`x` not equal to `expected`.
2/2 mismatches (average diff: 1.05)
[1] 0 - -1.400 == 1.400
[2] 0 - 0.703 == -0.703
-- 5. Failure: guess.scale handles relative effect data (@test-unit-allpairs.R#7
`x` not equal to `expected`.
1/1 mismatches
[1] 0 - 2.3 == -2.3
-- 6. Failure: guess.scale not confused by unrealized study levels (@test-unit-a
`x` not equal to `expected`.
1/1 mismatches
[1] NA - 1.08 == NA
-- 7. Failure: guess.scale not confused by unrealized study levels (@test-unit-a
`x` not equal to `expected`.
1/1 mismatches
[1] 0 - 1 == -1
-- 8. Error: single pair-wise comparison gives FALSE (@test-unit-has.indirect.ev
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 9. Error: comparison in triangle gives TRUE (@test-unit-has.indirect.evidence
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 10. Error: comparison in three-arm trial gives FALSE (@test-unit-has.indirect
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 11. Error: four-arm trials are handled correctly (@test-unit-has.indirect.evi
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 12. Error: data.re is incorporated (@test-unit-has.indirect.evidence.R#101)
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. testthat::expect_that(...)
6. gemtc:::has.indirect.evidence(network, "A", "B")
7. gemtc::mtc.network(data)
8. gemtc:::mtc.network.validate(network)
9. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 13. Error: Vertices agree between mtc.comparisons and the model tree (@test-u
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc::mtc.model(network)
2. gemtc:::mtc.model.call("mtc.model", model, ...)
4. gemtc:::mtc.model.consistency(...)
17. gemtc:::mtc.network.graph(model[["network"]])
18. gemtc:::comp(network)
20. base::`[<-.factor`(...)
-- 14. Error: mtc.comparisons.baseline identical to mtc.comparisons for two-arm
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 15. Error: mtc.comparisons.baseline only includes baseline comparisons for mu
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 16. Error: Vertices agree between mtc.network.graph and ume model$graph (@tes
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::mtc.network.graph(network)
2. gemtc:::comp(network)
4. base::`[<-.factor`(...)
-- 17. Error: RE data will not introduce duplicate basic parameters (@test-unit-
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 18. Error: the model generates correctly (@test-unit-mtc.model.use.R#12) ---
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 19. Error: std.dev + sampleSize is rewritten to std.err (@test-unit-mtc.model
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 20. Error: data.ab missing sampleSize throws error (@test-unit-mtc.model_colu
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 21. Error: data.ab missing std.dev throws error (@test-unit-mtc.model_columns
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 22. Error: data.ab missing mean throws error (@test-unit-mtc.model_columns.R#
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 23. Error: data.ab with std.err does not throw error (@test-unit-mtc.model_co
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 24. Error: mtc.model.data runs on simple data (@test-unit-mtc.model_data.R#8)
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 25. Error: mtc.model.data complains about NAs in data.ab (@test-unit-mtc.mode
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 26. Error: mtc.model.data includes correct fields for data.ab, binom.logit (@
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 27. Error: mtc.model.data includes correct fields for data.ab, binom.cloglog
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 28. Error: mtc.model.data includes correct fields for data.ab, poisson.log (@
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 29. Error: mtc.model.data includes correct fields for data.ab, normal.identit
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 30. Error: mtc.model.data includes correct fields for data.ab, normal.identit
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 31. Error: mtc.model.data includes correct fields for data.ab, binom.logit +
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 32. Error: mtc.model.data omits studies with alpha=0 (powerAdjust) (@test-uni
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re, studies = studies)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 33. Error: mtc.model.data has correct values (1) (@test-unit-mtc.model_data.R
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 34. Error: mtc.model.data has correct values (2) (@test-unit-mtc.model_data.R
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 35. Error: not specifying likelihood / link generates warnings (@test-unit-mt
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_warning(...)
6. gemtc::mtc.model(network, likelihood = "normal")
7. gemtc:::mtc.model.call("mtc.model", model, ...)
9. gemtc:::mtc.model.consistency(...)
22. gemtc:::mtc.network.graph(model[["network"]])
23. gemtc:::comp(network)
25. base::`[<-.factor`(...)
-- 36. Error: mtc.model refuses duplicated arms (@test-unit-mtc.model_duparm.R#4
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(...)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 37. Error: mtc.init.mle.regression just returns 0 +/- om.scale (@test-unit-mt
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 38. Error: mtc.linearModel.matrix works correctly (@test-unit-mtc.model_inits
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 39. Error: mtc.linearModel.matrix works correctly for regression (@test-unit-
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 40. Error: likelihood.arm.list returns the correct arms (@test-unit-mtc.model
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 41. Error: mtc.model.inits has correct shape (@test-unit-mtc.model_inits.R#24
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 42. Error: mtc.model.inits - regression parameters have the correct shape (@t
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, studies = studies)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 43. Error: mtc.model.inits has correct heterogeneity parameter (@test-unit-mt
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 44. Error: mtc.init correctly restrains the baseline probability (@test-unit-
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(read.csv("../data/rr-pairwise.csv"))
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 45. Error: treatments for data.ab and data.re are merged (@test-unit-mtc.netw
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 46. Error: merged list of arms is correct (@test-unit-mtc.network_data.re.R#8
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 47. Error: mtc.nr.comparisons with a single study (@test-unit-mtc.nr.comparis
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 48. Error: mtc.nr.comparisons with 2 studies (@test-unit-mtc.nr.comparisons.R
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 49. Error: mtc.study.treatment.matrix with 1 study (@test-unit-mtc.study.trea
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 50. Error: mtc.study.treatment.matrix with 2 studies (@test-unit-mtc.study.tr
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 51. Error: non-lexicographical treatment order works correctly (@test-unit-no
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, treatments = treatments)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 52. Error: study names do not mess up nodesplit with RE data (@test-unit-node
NAs are not allowed in subscripted assignments
Backtrace:
1. testthat::expect_that(...)
6. gemtc::mtc.nodesplit.comparisons(network)
8. gemtc:::mtc.comparisons(network)
10. base::`[<-.factor`(...)
-- 53. Error: mixing AB and RE data will not duplicate comparisons (@test-unit-n
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. gemtc::mtc.network(data.ab = data.ab, data.re = data.re)
2. gemtc:::mtc.network.validate(network)
3. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 54. Error: read.mtc.network('luades-smoking.gemtc') has expected result (@tes
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. testthat::expect_that(read.mtc.network(file), equals(smoking))
6. gemtc::read.mtc.network(file)
7. gemtc::mtc.network(data.ab, treatments = treatments, description = description)
8. gemtc:::mtc.network.validate(network)
9. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 55. Error: read.mtc.network('parkinson.gemtc') has expected result (@test-uni
all(all.treatments %in% network[["treatments"]][["id"]]) is not TRUE
Backtrace:
1. testthat::expect_that(read.mtc.network(file), equals(parkinson))
6. gemtc::read.mtc.network(file)
7. gemtc::mtc.network(data.ab, treatments = treatments, description = description)
8. gemtc:::mtc.network.validate(network)
9. base::stopifnot(all(all.treatments %in% network[["treatments"]][["id"]]))
-- 56. Error: tree.relative.effect handles a more complex tree (@test-unit-relat
NAs are not allowed in subscripted assignments
Backtrace:
1. gemtc:::minimum.diameter.spanning.tree(mtc.network.graph(network))
8. gemtc:::mtc.network.graph(network)
9. gemtc:::comp(network)
11. base::`[<-.factor`(...)
== testthat results ===========================================================
[ OK: 230 | SKIPPED: 2 | WARNINGS: 0 | FAILED: 56 ]
1. Failure: two pairs return a two-row matrix (@test-unit-allpairs.R#20)
2. Failure: calculating pairs for relative effect data transforms the mvnorm (@test-unit-allpairs.R#33)
3. Failure: calculating pairs for relative effect data handles 1-pair case (@test-unit-allpairs.R#46)
4. Failure: calculating pairs for relative effect data handles missing treatments (@test-unit-allpairs.R#60)
5. Failure: guess.scale handles relative effect data (@test-unit-allpairs.R#76)
6. Failure: guess.scale not confused by unrealized study levels (@test-unit-allpairs.R#82)
7. Failure: guess.scale not confused by unrealized study levels (@test-unit-allpairs.R#86)
8. Error: single pair-wise comparison gives FALSE (@test-unit-has.indirect.evidence.R#7)
9. Error: comparison in triangle gives TRUE (@test-unit-has.indirect.evidence.R#19)
1. ...
Error: testthat unit tests failed
In addition: Warning message:
In extract_lang(f = comp_lang, y = quote(if (.isMethodsDispatchOn() && :
devtools is incompatible with the current version of R. `load_all()` may function incorrectly.
Execution halted
Flavor: r-devel-windows-ix86+x86_64