Re: [R] Multilevel logistic regression using lmer vs glmmPQL vs.gllamm in Stata

From: Bernd Weiss <bernd.weiss_at_uni-koeln.de>
Date: Thu 04 Aug 2005 - 16:11:37 EST


Am 3 Aug 2005 um 18:02 hat ronggui geschrieben:

> >On Wed, 3 Aug 2005, Bernd Weiss wrote:
> >
> >> I am trying to replicate some multilevel models with binary
> >> outcomes using R's "lmer" and "glmmPQL" and Stata's gllmm,
> >> respectively.

[...]

> the glmmPQL and lmer both use the PQL method to do it ,so can we get
> the same result by setting some options to the command?
>

Thanks to Prof. Ripley and ronggui for their answers.

To verify my findings I tried other datasets and simulated some data and compared the results between R and Stata. Everything works fine, no differences -- except for the xerop-dataset.

Having a closer look to the R output I found some unusual values for AIC, BIC and deviance, see below:

           AIC BIC logLik deviance  1.797693e+308 1.797693e+308 -8.988466e+307 1.797693e+308

I assume I have to change some of the lmer-parameters but have absolutely no idea which one.

Again, I would appreciate any help.

Bernd



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