On Sep 9, 2010, at 8:50 PM, andre bedon wrote:
I am attempting to graph a Kaplan Meier estimate for some claims
using the survfit function. However, I was wondering if it is
possible to plot a cdf of the kaplan meier rather than the survival
function. Here is some of my code:
It's not really the cdf of the KM since the KM is just an estimator.
Yeah, I know, picky, picky.
library(survival)
Surv(claimj,censorj==0)
I'm reasonably sure you need to assign that to something (unless its
purpose is just to test the syntax.)
survfit(Surv(claimj,censorj==0)~1)
surv.all<-survfit(Surv(claimj,censorj==0)~1)
summary(surv.all)
plot(surv.all)
I would really appreciate any assistance. Thank you.
The survival function is just 1 minus the CDF, (and vice versa). You
didn't provide any data, but we can use the aml dataframe in survival:
library(survival)
surv.all<-survfit(Surv(time,status)~1, data=aml)
str(surv.all) # x-coord is "time" and S_KM(t) is "surv"
plot(surv.all$time, 1-surv.all$surv, type="s", ylim=c(0,1))
So that's the KM estimator of the CDF. Doesn't inherit the nice
features of the plot.survfit function, though. It's also going to be
more messy if you have two/+ groups
--
David Winsemius, MD
West Hartford, CT
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