The survfit function, when applied to the results of a Cox model, will give
the predicted survival curve for any particular combination of covariates in
the
model. You cannot get what you are asking for, i.e., distinct levels of X
while
ignoring Y, from survfit. What you need to do is create a data frame
containing
values for the curves that you want, e.g.,
mydata <- data.frame(X=c(1,2,3,4), y=c(8,8,8,8))
cfit <- survfit(mod.phm, newdata=mydata)
plot(cfit, lty=1:4)
People often choose a 'common' value of y for the plot.
Arguably the better approach is to average over the levels of y. For this, I
would recommend that you read chapter 10 of Therneau and Grambsch, Modeling
Survival Data. The discussion really does take a whole chapter, and is too
long
for a help-list synopsis.
Terry Therneau
------------------------------------------------------------
begin included message
Thanks for your help. I want to draw a plot which shows separate
survival curves for each category of X on the same plot(same set of
axes). Your code produces a separate curve for each combination of X
and Y but I don't want curves for combinations of X and Y since Y has
many levels and also the values of Y don't have any significance in my
case. Is there a way of doing what i want to do i.e. getting separate
survival curves for each level of X using the function survfit() on an
object mod.phm which is a coxph object such that:
mod.phm<-coxph(formula=Surv(time,Flag_Death)~X+Y, data= datFrame)
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
