R help - Dec 2006 - Passing arguments to panels in trellis plots

Dear all,

I am trying to produce survfit plots in a trellis environment and I
would like the plots to be logarithmic.

I am trying this:

print(Ecdf(~time | size*type, groups=alg,data=B,subscripts=TRUE,
            panel=function(x,groups,subscripts)
            {
              t <-
survfit(Surv(time[subscripts],event[subscripts])~groups[subscripts],data=B)
              panel.xyplot(t[1]$time,1-t[1]$ssurv,type="s",lty=2)
              panel.xyplot(t[2]$time,1-t[2]$ssurv,type="s",lty=2)
            },
 	   scale=list(log=TRUE)
)



but data are transformed in logarithm before being passed to the panel
and hence the output of the function survfit is not the expected one.

Is there a way to plot this correctly, ie, having first the survfit
computed and then the plot, like in:

plot(survfit(Surv(time,event)~groups,data=B),log=true)

Thanks in advance.

- Marco.


--
Marco Chiarandini                     http://www.imada.sdu.dk/~marco
Department of Mathematics	      Email: marco AT imada.sdu.dk
and Computer Science,		      Phone: +45 6550 4031
University of Southern Denmark        Fax: +45 6593 2691

On 12/13/06, Marco Chiarandini <marco at imada.sdu.dk>
wrote:
> Dear all,
>
> I am trying to produce survfit plots in a trellis environment and I
> would like the plots to be logarithmic.
>
> I am trying this:
>
> print(Ecdf(~time | size*type, groups=alg,data=B,subscripts=TRUE,
>             panel=function(x,groups,subscripts)
>             {
>               t <-
survfit(Surv(time[subscripts],event[subscripts])~groups[subscripts],data=B)
>               panel.xyplot(t[1]$time,1-t[1]$ssurv,type="s",lty=2)
>               panel.xyplot(t[2]$time,1-t[2]$ssurv,type="s",lty=2)
>             },
>            scale=list(log=TRUE)
> )
>
>
>
> but data are transformed in logarithm before being passed to the panel
> and hence the output of the function survfit is not the expected one.
>
> Is there a way to plot this correctly, ie, having first the survfit
> computed and then the plot, like in:
>
> plot(survfit(Surv(time,event)~groups,data=B),log=true)
Since you haven't bothered to follow the posting guide at all, it took
me a while to figure out that you live in that alternate R universe
created by Prof Harrell. Can't help you there, but in the standard
universe, things seem fairly simple:


library(survival)

fm <- survfit(Surv(time, status) ~ x, data=aml)

xyplot(surv ~ time, data = fm, type = "s",
       groups = rep(names(strata), strata))

xyplot(surv ~ time, data = fm, type = "s",
       groups = rep(names(strata), strata),
       scales = list(log = TRUE))

xyplot(surv + lower + upper ~ time | rep(names(strata), strata),
       data = fm, type = "s",
       scales = list(y = list(log = TRUE)))

-Deepayan