Multilevel logistic regression using lmer vs glmmPQL vs.gllamm in Stata

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