I have an update for this question. Now that I have figured out how to do
this correctly I have a new question.
Is there a way to deal with late entries (left truncation) for competing
risk analysis in R? For so-called period analyses?
I apologize if I haven't provided enough information. I will be happy to
do so.
Best,
Jen
On Mon, Feb 27, 2012 at 11:09 PM, Jennifer Sabatier <
plessthanpointohf...@gmail.com> wrote:
> Hi Rs,
>
> I am analyzing a time to event dataset with several competing risks.
>
> 0 = Active by end of study
> 1 = Stopped treatment to start another treatment
> 2 = Lost
> 3 = Dead
>
> My event of interest in Lost to Followup but starting a different
> treatment and dying are competing risks. All 1,2,3 events are events of
> exiting the study, but it's only 2-LTFU that we are concerned with (I know
> I am repeating myself, sorry).
>
> I can't seem to find a package or function that can handle 2 competing
> risks for the main event. I realize I may be using the well-known ones,
> timereg and cmprisk, wrong. And if I am, then I'd appreciate a correction.
>
> Here's the model I tried (and it crashes)
>
> comp.risk(Surv(futime, retention==2) ~ sex, data=dta, dta$retention,
> causeS=c(1,3), resample.iid=1, n.sim=100)
>
> I apologize, but I am cannot create the example dataset using code. I am
> not able.
>
> The data, though is one to one.
>
> ID retention sex futime
> ------------------------------------
> 1 0 1 524.3
>
>
> etc.
>
> Thank you, in advance, if you can help me.
>
> Best,
>
> Jen
>
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