[R-sig-ME] overdispersion in GLMMs (Alejandro Mart?nez Abra?n)
ecrone at fas.harvard.edu
Thu Jul 19 16:34:39 CEST 2012
> 1. How can I estimate overdispersion in a Poisson GLMMM?
I usually fit overdispersed Poisson (or Binomial) GLMMs by adding a
unique identifier for each observation, then adding that unique ID as
a random term. You can "test" how overdispersed the model is by
looking at the standard deviation assoicated with that random effect,
or by comparing the fit of a model with the overdispersion term to one
Alternatively, you can look at overdispersion due to random effects of
individual, plot, etc, using the same basic procedure.
I think I got the idea from the Gelman et al. Bayesian stats text. I
would be curious to know if others do this also.
> 2. I am trying to run a quasipoisson GLMM using the lmer function and the
> lme4 library but I get a
> warning stating that "glmer cannot deal with quasi error families? Any tip?
> because I have seen this done.
My understanding is that this functionality has been removed, since it
is +/- redundant with the approach used above, but less naturally
linked to the mixed model framework.
Elizabeth E. Crone
Senior Ecologist, Harvard Forest
Petersham MA 01366
email: ecrone at fas.harvard.edu
More information about the R-sig-mixed-models