coxphQuantile function

Survival time quantile as a function of covariate

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

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.

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)
## End(Not run)

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.