st: survival analysis in the presence of competing risks and multi-level data

[Salah Mahmud <salah.mahmud@gmail.com>]

Hello,
Just wondering if anyone is aware of reasonable approaches (preferably
implementable in Stata) to fit competing risks time-to-event models to
clustered data.

I have a dataset where participants are clustered by family and
eventually by locality. The outcome is time to first hospitalization
due to a certain condition, but observing this outcome could be
precluded by death. So I would like to account for these competing
risks  because my predictors will likely influence all outcomes.
Normally I would use something like Fine & Gray models, but the data
are clustered at more than one level and I would like to model the
effects of covariates measured at different levels (and not just
adjust my SE for correlation, eg, using robust SE estimates). Is there
a way of fitting this model in Stata (eg, using gllamm)? in a
different package?

Thanks,
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