R help - Oct 2012 - Assessing overdispersion and using quasi model with lmer, possible?

Hello! 
I am trying to model data on species abundance (count data) with a poisson
error distribution. I have a fixed and a random variables and thus needs a
mixed model. I strongly doubt that my model is overdispersed but I don't
know how to get the overdispersion parameter in a mixed model. Maybe someone
can help me on this point. Secondly, it seems that quasi models cannot be
implemented with the function lmer, is there an option? If not, I certainly
should go to variable transformation and use a gaussian error distribution,
but it is not optimal.
Thank you!



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swertie <v_coudrain <at> voila.fr> writes:
> I am trying to model data on species abundance (count data) with a poisson
> error distribution. I have a fixed and a random variables and thus needs a
> mixed model. I strongly doubt that my model is overdispersed but I
don't
> know how to get the overdispersion parameter in a mixed model. Maybe
someone
> can help me on this point. Secondly, it seems that quasi models cannot be
> implemented with the function lmer, is there an option? If not, I certainly
> should go to variable transformation and use a gaussian error distribution,
> but it is not optimal.
  You should read the section in http://glmm.wikidot.com/faq on
overdispersion, and address further questions to the
r-sig-mixed-models <at> r-project.org mailing list ...

  Ben Bolker

thank you very much



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