On Fri, Nov 7, 2008 at 11:03 AM, <[EMAIL PROTECTED]> wrote: > Dear R Users,
> May be this message should be directy send to Douglas Bates ... > I just want to know if I can use the AIC value given in the output of an lmer > model to classify my logistic models. > I heard that the AIC value given in GLIMMIX output (SAS) is false because it > come from a calculation based on pseudo-likelyhood. > Is it the same for lmer ??? I don't know about the situation with SAS. The AIC value returned by lmer is based on an approximation to the integral of the conditional density of the random effects. I had thought that I could evaluate that conditional density from the sum of the deviance residuals for the glm family but, given some recent discussion on the R-SIG-Mixed-Models mailing list regarding the quasibinomial and quasipoisson families, i am starting to doubt that. So the quantity that is returned is based on something that is more like the likelihood than is the pseudo-likelihood but may not be the actual likelihood. I do plan to change the value returned to be the likelihood for the gaussian, binomial, poisson and Gamma families. I don't know what to do about the quasi families. As far as I can see there isn't a likelihood for those families because they don't represent a probability distribution. I am cc:ing the R-SIG-Mixed-Models mailing list on this reply. I suggest we move further discussion, if any, to that list. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
