On Mar 23, 2014, at 9:14 PM, Lucy Leigh wrote:
> Hi everyone,
>
> I am currently attempting to simulate some survival data, based on a Weibull
> model. I basically need to simulate some survival data
> so that I can then test out a program I'm writing, before applying it to some
> real data.
>
> I've managed to create failure time data, using the rweibull function. I.e.
> Y[i] <- rweibull(1, shape, scale)
> For a variety of shape and scale parameters etc.
>
> I wish to add in right censoring. If I am considering my failure times as
> deaths, and the censoring time
> as a study cut-off date (for example, 5 years from baseline), would it be
> correct to do something like,
>
> for(i in 1:nSubjects){
> if (Y[i] > 5){
> Y[i] <- 5}
> else
> {Y[i] <- Y[i]
> }}
>
This would be more R-ish if you did it this way (loop-free)
Y[ Y > 5 ] <- 5 # set cutoff
cens.time <- runif(length(Y), 0, max(Y) )
cens <- cens.time < Y
survreg( Surv(Y, !cens) ~ 1 )
Untested (well, lightly tested) in absence of data object.
> I guess my question is, is it statistically sound to impose the right
> censoring after estimating the distribution with no censoring?
> I am leaning towards yes, because in an ideal world where we followed all
> participants until they died, the
> distribution would be as estimated by the rweibull above....and assuming that
> the right censoring is independent,
> then cutting of the measurements at a pre-specified time wouldn't affect the
> outcome at all. But I guess I am
> just looking for a second opinion?
>
> Thanks in advance, this list has been immensely helpful with some previous
> questions I have had about
> the survival package.
> Lucy
>
Please post in plain text.
> [[alternative HTML version deleted]]
--
David Winsemius
Alameda, CA, USA
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