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From |
Nick Cox <njcoxstata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Tue, 26 Mar 2013 20:32:56 +0000 |

Good that you seem to be making progress. Just to comment on a side detail: I see no grounds for thinking that cloglog link implies a discrete response. In principle, it could make sense for continuous proportions too. As I recall, the original application (R.A. Fisher, no less) was for precisely this purpose. Nick On Tue, Mar 26, 2013 at 8:01 PM, Karen Ruckman <ruckman@sfu.ca> wrote: > thanks guys for the information. i see that the loglog link is not the same thing as the loglog distribution in survival analysis. (even though the loglog link is not actually listed anywhere...i digress.) i most definitely was not looking to run a cloglog. that was suggested by someone else. i do not have a discrete dependent variable, so cloglog is not appropriate. > > tricking -gllamm- to use poisson was exactly what i was after. in the gllamm manual on p.80, the authors give two commands, both the equivalent of each other: > streg secondp after decl, dist(exp) > poisson unceni secondp after decl, offset(lny) irr > > they do not show it but claim they would produce identical results. i would use the same (although in the -gllamm- command) except the problem is my underlying survival analysis hazard rate doesn't have an exponential structure. i use a log-logistic structure but log-normal would be fine too. i am unsure how to get this to work in -poisson- or in -gllamm-. > > > > ----- Original Message ----- > From: "JVerkuilen (Gmail)" <jvverkuilen@gmail.com> > To: statalist@hsphsun2.harvard.edu > Sent: Tuesday, March 26, 2013 12:42:30 PM > Subject: Re: st: equivalence of log-logistic survival estimation with gllamm > > 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/ > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/statalist-faq/ > * http://www.ats.ucla.edu/stat/stata/ > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/statalist-faq/ > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: equivalence of log-logistic survival estimation with gllamm***From:*"JVerkuilen (Gmail)" <jvverkuilen@gmail.com>

**Re: st: equivalence of log-logistic survival estimation with gllamm***From:*Karen Ruckman <ruckman@sfu.ca>

**References**:**Re: st: equivalence of log-logistic survival estimation with gllamm***From:*"JVerkuilen (Gmail)" <jvverkuilen@gmail.com>

**Re: st: equivalence of log-logistic survival estimation with gllamm***From:*Karen Ruckman <ruckman@sfu.ca>

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