clinfun (version 1.0.14)

coxphQuantile: Survival time quantile as a function of covariate

Description

Draws a quantile curve of survival distribution as a function of covariate.

Usage

coxphQuantile(phfit, xrange, p=0.5, whichx=1, otherx=NULL, ...)

Arguments

phfit

output from a proportional hazards fit.

xrange

the range of covariate values for which the quantiles of survival times are computed.

p

the probability level for the quantile (default is median).

whichx

if there are more than one covariates in the Cox model, the one chosen for the quantile plot.

otherx

the values for other covariates in the Cox model. If missing uses their average values.

...

additional parameters to be passed on to the lines command.

Details

This function is used to draw quantile curves. It requires a plot of the data (time & covariate of interest) to be present. See example.

It invisibly returns the observed failure times and the covariate values at which the estimated survival probability is (exactly) p.

References

Heller G. and Simonoff J.S. (1992) Prediction in censored survival data: A comparison of the proportional hazards and linear regression models. Biometrics 48, 101-115.

Examples

# NOT RUN {
  library(survival)
data(pbc)
pbcfit <- coxph(Surv(time, status==2) ~ trt + log(copper), pbc,
                      subset=(trt>0 & copper>0)) 
plot(log(pbc$copper[pbc$trt>0 & pbc$copper>0]), pbc$time[pbc$trt>0 &
  pbc$copper>0], pch=c("o","x")[1+pbc$status[pbc$trt>0 & pbc$copper>0]], 
  xlab="log Copper", ylab="Survival time")
coxphQuantile(pbcfit, c(2.5,6), whichx=2, otherx=1)
coxphQuantile(pbcfit, c(2.5,6), p=0.75, whichx=2, otherx=2, col=2)
# }