Hi Bernhard,
I'm wondering what you will expect to get in "dividing" two proportional
survival curves from a fitted cox model.
Anyway, you can provide a newdata object to the survfit function
containing any combination of cofactors you are interested in and then
use summary, eg:
fit <- coxph( Surv(futime,fustat)~resid.ds+rx+ecog.ps,data=ovarian)
summary(survfit( fit,newdata=data.frame(rx=1, ecog.ps=2, resid.ds=0)))
hth.
Bernhard Reinhardt schrieb:
Hi!
I came across R just a few days ago since I was looking for a toolbox
for cox-regression.
I´ve read
"Cox Proportional-Hazards Regression for Survival Data
Appendix to An R and S-PLUS Companion to Applied Regression" from John
Fox.
As described therein plotting survival-functions works well
(plot(survfit(model))). But I´d like to do some manipulation with the
survival-functions before plotting them e.g. dividing one
survival-function by another.
survfit() only returns an object of the following structure
n events median 0.9LCL 0.9UCL
55.000 55.000 1.033 0.696 1.637
Can you tell me how I can calculate a survival- or baseline-function
out of these values and how I extract the values from the object? I´m
sure the calculation is done by the corresponding plot-routine, but I
couldn´t find that one either.
Regards
Bernhard
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