GLMM with binomial error and individual-level, random term
Highland Statistics Ltd <highstat at ...> writes:
Message: 3 Date: Sat, 26 Jan 2013 19:02:21 +0100 (CET) From: v_coudrain at ... Subject: [R-sig-ME] GLMM with binomial error and individual-level random term
I performed a GLMM with binomial error and individual-level random
term to account for overdispersion. I If I understood it correctly on http://glmm.wikidot.com/faq, > denominator df are not defined for such models and the significance of the parameters should be tested using Chi-square tests. Is this correct? In F-test, results are > generally reported by giving the numerator and denominator df, the F value and the p value. Hiw should I report the results of my model? Additionally I would like to > ask if somebody has relevant literature associated to the addition of an individual-level randorm term to account for overdispersion.
Have a look at a paper from Dave Elston:
[snip] [also referenced from the http://glmm.wikidot.com/faq page, along with other refs, as previously described]
It is also in Chapter 2 in Zuur et al. (2012)...sorry for self-citing. I think I would try a beta binomial GLMM in JAGS. I believe Ben has written a package for beta binomial GLM. Not sure whether it can do GLMM. I think gamlss can also do beta binomial GLMM...not sure.
There are a number of packages that can do beta-binomial GLM -- bbmle makes it fairly straightforward, although it's not specifically for beta-binomial GLMs. Probably also the VGAM and aod packages. glmmADMB doesn't do beta-binomial GLMMs, but could fairly easily be extended to do so. I'd be happy to accept high-quality patches ... or a compelling reason to spend my time on it right now ...
We are co-authoring a book with Joe Hilbe in which we have a 40 page chapter where we compare binomial GLMM with the individual level random effect and the beta binomial GLMM. ....... 'Beginner's Guide to GLM and GLMM using R and JAGS'. Comes out in 2-3 months....sorry for self-advertising...
Seems reasonable if it answers the question.