I'm dealing with count data that's nested and has spatial dependence. I ran a glmm in lmer with a random factor for nestedness. Spatial dependence seems to have been accommodated by model. However I can't add a variance strcuture to this model (to accommodate heterogeneity).
Is there a model that can have a poisson distribution *AND* a variance structure *AND* have AIC in output (for model comparison and selection)? Some we've looked at that can't: - glmmPQL - can add structures BUT can't have AIC (you can calculate it but it doesn't give correct AIC with this model) - glmm in lme4 (lmer) - won't allow variance structure - gls - can add variance but can't have Poisson Thanks so much, Karen Moore PhD Researcher, FORESTBIO, Department of Botany, Trinity College Dublin Ireland [[alternative HTML version deleted]] ______________________________________________ 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.