Thanks David. I’m not sure I completely follow. Are you referring to sandwich type estimators like that implemented by using cluster() instead of a frailty term? Could you please also clarify your last sentence?
On Feb 12, 2015, at 10:52 PM, David Winsemius <dwinsem...@comcast.net> wrote: > > On Feb 12, 2015, at 5:50 PM, Steve Bellan wrote: > >> Hi all, I'm fitting a coxph gamma frailty model to simulated survival data >> and running into situations where I have 0 events in one covariate class and >> the model won't converge. I'd still like a p-value in those cases as this is >> part of a power analysis. With enough person-time observed 20 events in one >> group and 0 in another is likely significant, but I want a p-value to be >> sure. Firth's correction in ‘coxphf’ seems appropriate but coxphf doesn't >> seem to deal with random effects. Any suggestions would be much appreciated! >> > > I would have expected power analyses in mixed model situations to be > conducted with bootstrap methods. In that setting you could just collect the > zero event cases in one category and use then as part of the denominator. > > -- > > David Winsemius > Alameda, CA, USA > _______________________________________________ R-sig-Epi@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-epi
