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Re: st: equivalence of log-logistic survival estimation with gllamm


From   "JVerkuilen (Gmail)" <jvverkuilen@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: equivalence of log-logistic survival estimation with gllamm
Date   Tue, 26 Mar 2013 15:42:30 -0400

On Tue, Mar 26, 2013 at 2:43 PM, Nick Cox <njcoxstata@gmail.com> wrote:

>
> The loglog and cloglog link functions have no application to survival
> times whatsoever. They are relevant _only_ to mean responses bounded
> by 0 and 1.

I'm with Nick. It's pretty clear there's some confusion going on.

However, there are discrete time proportional hazards survival models
that involve the cloglog link, and maybe that's what the original
poster wanted? I just checked Multilevel and Logitudinal Modeling
Using Stata, Volume II: Categorical Responses, Counts, and Survival,
Third Edition, S. Rabe-Hesketh and A. Skrondal, 2012, Stata Press.
They give an example using -xtcloglog- on p. 783, and discuss how this
could be fit using -gllamm-.

For a continuous time parametric survival model, I'm guessing that
some kind of censored normal model on the log-transformed time would
be necessary. That would be the lognormal model, not the log-logistic.
Out of my area, but I wonder if it would be possible to trick -gllamm-
to use the same basic "Poisson" likelihood discussed here, but with
censoring?

http://blog.stata.com/2011/08/22/use-poisson-rather-than-regress-tell-a-friend/
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