phcpe {CPE} | R Documentation |
A function to calculate Gonen & Heller concordance probability estimate (CPE) for the Cox proportional harzards model.
phcpe(coxfit, CPE.SE=FALSE,out.ties=FALSE)
coxfit |
a coxph or cph object |
CPE.SE |
a logical value indicating whether the standard error of the CPE should be calculated |
out.ties |
If out.ties is set to FALSE,pairs of observations tied on covariates will be used to calculate the CPE. Otherwise, they will not be used. |
CPE |
Concordance Probability Estimate |
CPE.SE |
the Standard Error of the Concordance Probability Estimate |
Qianxing Mo, Mithat Gonen and Glenn Heller; moq@mskcc.org
Mithat Gonen and Glenn Heller. (2005). Concordance probability and discriminatory power in proportional hazards regression. Biometrika, 92, 4, pp.965-970
### create a simple data set for testing set.seed(199) nn <- 1000 time <- rexp(nn) status <- sample(0:1, nn, replace=TRUE) covar <- matrix(rnorm(3*nn), ncol=3) survd <- data.frame(time, status, covar) names(survd) <- c("time","status","x1","x2","x3") library(survival) coxph.fit <- coxph(Surv(time,status)~x1+x2+x3,data=survd) ### Calculate CPE only (needs much less time). library(CPE) phcpe(coxph.fit) phcpe(coxph.fit,out.ties=TRUE) #result is identical because the covariates are not tied # ### Calculate CPE and CPE.SE phcpe(coxph.fit, CPE.SE=TRUE) phcpe(coxph.fit, CPE.SE=TRUE,out.ties=TRUE) #*** For unknown reason, 'coxph.fit' may need to be removed before running cph()*** rm(coxph.fit) library(Design) cph.fit <- cph(Surv(time, status)~x1+x2+x3, data=survd,method="breslow") ### Calculate CPE only (needs much less time). phcpe(cph.fit) phcpe(cph.fit,out.ties=TRUE) ### Calculate CPE and CPE.SE phcpe(cph.fit, CPE.SE=TRUE) phcpe(cph.fit, CPE.SE=TRUE,out.ties=TRUE)