
   Dear list members:

   I am implementing some models using count data with lmer. I would like to 
check for overdispersion to know if I have to change the family in the model. 
But obviously, lmer does not return the standard error and the degrees of 
freedom of the model, like glm does, and I've seen in another post that older 
versions of lmer used to give an estimate of the scale parameter, whose 
deviation from 1 could be used as an overdispersion check. The version of R I'm 
using does not give this estimation, and I'm wondering why this is so. 

   I´ve found as well a way of calculating it by hand, with this formula:
   
   sqrt(sum(c(fm1 at resid, fm1 at u)^2)/length(fm1 at resid))

   where "fm1" is the name of the model to check. But I don't know how to write 
it so that it returns an appropriate value in R. 


   Also, I was wondering wether this term is not showed in lmer any more because 
lmer can deal with overdispersion better than glm, or there´s another reason.

   Any help will be highly appreciated. 
   Thank you very much.

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