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

[Bernd Weiss]

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