Message-ID: <200504171131.25097.deepayan@stat.wisc.edu>
Date: 2005-04-17T16:31:25Z
From: Deepayan Sarkar
Subject: generalized linear mixed models - how to compare?
In-Reply-To: <1113745148.426266fc2f9ac@webmail.ufz.de>
On Sunday 17 April 2005 08:39, Nestor Fernandez wrote:
> Dear all,
>
> I want to evaluate several generalized linear mixed models, including
> the null model, and select the best approximating one. I have tried
> glmmPQL (MASS library) and GLMM (lme4) to fit the models. Both result
> in similar parameter estimates but fairly different likelihood
> estimates.
> My questions:
> 1- Is it correct to calculate AIC for comparing my models, given that
> they use quasi-likelihood estimates? If not, how can I compare them?
> 2- Why the large differences in likelihood estimates between the two
> procedures?
The likelihood reported by glmmPQL is wrong, as it's the likelihood of
an incorrect model (namely, an lme model that approximates the correct
glmm model). GLMM uses (mostly) the same procedure to get parameter
estimates, but as a final step calculates the likelihood for the
correct model for those estimates (so the likelihood reported by it
should be fairly reliable).
Deepayan