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.
