# phcpe2: Gonen & Heller Concordance Probability Estimate for the Cox... In CPE: Concordance Probability Estimates in Survival Analysis

## Description

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

## Usage

 `1` ```phcpe2(coef,coef.var,design, CPE.SE=FALSE,out.ties=FALSE) ```

## Arguments

 `coef` The coefficients of the Cox model. `coef.var` The covariance matrix of the coefficients of the Cox model. `design` A design matrix for covariates. The rows correspond to subjects, and the columns correspond to covariates. `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; [email protected]

## References

Mithat Gonen and Glenn Heller. (2005). Concordance probability and discriminatory power in proportional hazards regression. Biometrika, 92, 4, pp.965-970

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21``` ```### 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) phcpe(coxph.fit,CPE.SE=TRUE) phcpe2(coef=coxph.fit\$coefficients,coef.var=coxph.fit\$var,design=model.matrix(coxph.fit)) #*** 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). phcpe2(cph.fit\$coefficients,coef.var=cph.fit\$var,design=model.matrix(cph.fit),CPE.SE=TRUE) ```

CPE documentation built on May 29, 2017, 9:11 a.m.