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

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