This shoul work:

coxph(Surv(intx, status) ~ . + strata(sex) - sex, test1)


On Wed, Aug 11, 2010 at 1:54 PM, Mendolia, Franco <fmendolia@mcw.edu> wrote:

> Hello!
>
> I have something like this:
>
> test1 <- data.frame(intx=c(4,3,1,1,2,2,3),
>                   status=c(1,1,1,0,1,1,0),
>                   x1=c(0,2,1,1,1,0,0),
>                   x2=c(1,1,0,0,2,2,0),
>                   sex=c(0,0,0,0,1,1,1))
>
> and I can easily fit a cox model:
>
> library(survival)
> coxph(Surv(intx,status) ~ x1 + x2 + strata(sex),test1)
>
> However, I want to write my own function, fit the model inside this
> function and then do some further computations.
>
> f <- function(time, event, stratum, covar )
> {
>
>  fit <- coxph(Surv(time,event) ~ covar[[1]] + covar[[2]] + strata(stratum))
>  fit
>  #... do some other stuff
> }
>
> attach(test1)
> f(intx, status, sex, list(x1,x2))
>
> This works fine when I have exactly two covariates. However, I would like
> to have something that I can use with an arbitrary number of covariates.
> More precisely, I need something more general than covar[[1]] + covar[[2]].
>
> Any ideas?
>
> Thanks,
> Franco
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>



-- 
Henrique Dallazuanna
Curitiba-Paraná-Brasil
25° 25' 40" S 49° 16' 22" O

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