phcpe {CPE}

Gonen and Heller Concordance Probability Estimate for the Cox Proportional Hazards model

Description

A function to calculate Gonen and Heller concordance probability estimate (CPE) for the Cox proportional hazards model.

Usage

phcpe(coxfit, CPE.SE=FALSE,out.ties=FALSE)

Arguments

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.

Value

CPE

Concordance Probability Estimate

CPE.SE

the Standard Error of the Concordance Probability Estimate

Author(s)

Qianxing Mo, Mithat Gonen and Glenn Heller; [e-mail]

References

Mithat Gonen and Glenn Heller. (2005). Concordance probability and discriminatory power in proportional hazards regression. Biometrika, 92, 4, pp.965-970 Glenn Heller and Qianxing Mo. (2016). Estimating the concordance probability in a survival analysis with a discrete number of risk groups. Lifetime Data Analysis, 22(2):263-79.

See Also

phcpe2

Examples

### 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")

coxph.fit <- coxph(Surv(time,status)~x1+x2+x3,data=survd)

### Calculate CPE only (needs much less time).
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)

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)