On Dec 4, 2009, at 9:29 AM, Ashta wrote:
> Hi All,
>
> I am trying to run the following script but have problem,
>
> coxm<- coxph(Surv(sdat$time, sdat$cens)~hd+nawtg+nwwg+ntpg+cy
> +nseas,data=sdat)
> coxm<-stepAIC(coxm,~.^2)
>
> The error message is
> Error: could not find function "stepAIC"
Perhaps you have not loaded the package that contains that function?
>
> I tried to install the package but I could not find it. Where can i
> get it?
>
>
> The other question is that I want to get the Kaplan-Meier Estimate
> for each covariate in the model,
Not exactly sure what that means. Kaplan-Meier estimate of ...
what?> Like
> covaraite n Events Mean, S.E.(mean) ,Median, 95% LCL, 95% UCL
> 0 14 10 2.87 .03 2.2
> 1.938 infi
> 1 11 9 1.06 .67 1.1
> 0.29 2.48
>
> I used
>
> sdat.fit0 <- survfit(Surv(sdat$time, sdat$cens)~sdat$ntpg, data =
> sdat,
> type = "kaplan-meier", conf.type="plain")
> sdat.fit0
>
> Instead I got the following,
>
>
> Call: survfit(formula = Surv(sdat$time, sdat$cens) ~ sdat$ntpg, data
> = sdat,
> type = "kaplan-meier", conf.type = "plain")
>
> records n.max n.start events median
> 0.95LCL 0.95UCL
> sdat$ntpg=0 3576 3576 3576 311 NA
> NA NA
> sdat$ntpg=1 4851 4851 4851 466 NA
> NA NA
If you have a dataset with 300-400 events out of 3000-4000 subject,
then why are you expressing surprise that you do not get a non-
parametric estimate of the median survival? The median is the time at
which half of the subjects would have experienced an event and you
only have 1/10 of them with events.
--
David Winsemius, MD
Heritage Laboratories
West Hartford, CT