survival::survfit,plot.survfit
Jeff Xu wrote:
I am confused when trying the function survfit. my question is: what does the survival curve given by plot.survfit mean? is it the survival curve with different covariates at different points? or just the baseline survival curve? for example, I run the following code and get the survival curve #### library(survival) fit<-coxph(Surv(futime,fustat)~resid.ds+rx+ecog.ps,data=ovarian) plot(survfit(fit,type="breslow")) summary(survfit(fit,type="breslow")) #### for the first two failure points, we have s(59|x1)=0.971, s(115|x2)=0.942 how can we guarantee that s(59|x1) is always greater than s(115|x2)? since s(59|x1)=s_0(59)^exp(\beta'x1) and s(115|x2)=s_0(115)^exp(\beta'x2), we can manipulate covariates to make s(59|x1) < s(115|x2), right? do I miss anything?
In advance: I?m a beginner in survival analysis, too. But I think I can help you with this. plot(survfit(fit)) should plot the survival-function for x=0 or equivalently beta'=0. This curve is independent of any covariates. If you want to see the impact of residual-status=2 you could add something like: attach(ovarian) ovarian_new <- data.frame(resid.ds=2, rx=(mean(rx)),ecog.ps=mean(ecog.ps)) detach() plot(survfit(fit), newdata=ovarian_new) This should give you the survival-function for an average patient with residual-status 2. Regards Bernhard