Hi everyone, I am fitting a cox proportional hazard model with a continuous variable "x" as the covariate:
fit<-coxph(Surv(time, status)~x) Now I wanted to make a plot of survival probability vs. the covariate, and the 95% confidence interval for the survival probability. It's just like a Kaplan-Meier Survival curve, except now the x axis represents the value of covariate, not the time. Someone gave me a reference to a paper in JASA by Gary (1992) for this type of plot, but I didn't have the access to the paper. So I am wondering if anyone knows how to do this in R or S-Plus? In addition, can anyone explain to me what are the following "type" options in predict.coxph() predicting? predict(fit,type='lp',se.fit=T) predict(fit,type='risk',se.fit=T) predict(fit,type='expected',se.fit=T) predict(fit,type='terms',se.fit=T) Thank you very much ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
