Dear all,

I hope my question will not be considered too simple to be asked here. I
will try to clearly explicit my problem.

I am working on longitudinal data to explore male reproductive success (rs).
These data are therefore count data and I deal with it by specifying in my
mixed models (random variable=individual identity) a poisson family.
My data present a large number of zeros, as shows the table() function
applyed to my response variable:

table(rs)
0   1   2   3   4   5   6   7
365  60  20   9   8   5   3   1


I am wondering :
1- if it matches with the description of an overdispersion or with a zero
inflated distribution.
2- how it is possible to calculate a c-hat, given that determining the
number of parameters in glmm is not an easy task...
3- if the realy bad fitted values obtained for the highest reproductive
success are the result of a first estimation with a poisson familly.


Thank you very much for the extra time and efforts you put in answering all
these questions.


Alexandre

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