survreg does work. Hard to tell what went wrong without any code from you.
As for smoothing a Cox survival function, see example below. However, just
because you can, doesn't mean you should.
Chris
library(survival)
nn <- 10
zz <- rep(0:1, nn)
xx <- rexp(2*nn)
cc <- rexp(2*nn)
tt <- pmin(xx, cc)
dd <- xx <= cc
mod <- coxph(Surv(tt,dd)~zz)
sf <- survfit(mod)
steps.y <- sf[[c("surv")]][c(1,1+which(diff(sf[[c("surv")]])<0))]
steps.x <- sf[[c("time")]][c(1,1+which(diff(sf[[c("surv")]])<0))]
plot(sf, conf.int=FALSE)
lines(steps.x, steps.y, col=2)
smoothfun <- approxfun(steps.x, steps.y)
plot(smoothfun, from=0, to=3, add=TRUE, col=3, n=1000, lty=2)
-----Original Message-----
From: Bond, Stephen [mailto:stephen.b...@cibc.com]
Sent: Thursday, January 17, 2013 9:49 AM
To: r-help@r-project.org
Subject: [R] coxph with smooth survival
Hello users,
I would like to obtain a survival curve from a Cox model that is smooth and
does not have zero differences due to no events for those particular days.
I have:
> sum((diff(surv))==0)
[1] 18
So you can see 18 days where the survival curve did not drop due to no events.
Is there a way to ask survfit to fit a nice spline for the survival??
Note: I tried survreg and it did not work, but maybe I did not do it properly??
Thank you very much.
Stephen B
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