[R] GlmmPQL with binomial errors

[O Tosas Auguet]

Hi all!

I hope somebody can help me solve some doubts which must be very basic, 
but I haven't been able to solve by myself.

The first one, is how to assess for overdispersion in GlmmPQL when fitting 
binomial or poisson errors. The second one is whether GlmmPQL can compare 
models with different fixed effects.

The third doubt, regards the way I should arrange my data in a GlmmPQL with 
binomial errors. In glm, I am supposed to create cbind vector joining 
the "number of successes" and the "total-the number of successes". Should I 
proceed the same way for GlmmPQL of can I use a single column which, intead of 
containing the numbers, simply contains 0 or 1?. The reason for this question, 
is that I am trying to fit a variance components analysis with a single random 
effect and no fixed effects. The only way I know to test for the significance 
of the single level of random effects is by comparing the model with a glm 
without fixed effects and do a ChiSquare test. So, should the data of both 
models be arranged the same way? or is it possible to compare the model with 
random effects and response "0,1" whith that of a glm without fixed effects 
where the response is arranged as cbind(successes,total-successes)? My concern 
of using cbind in GlmmPQL, is that lose replication of the variable of 
interest, and I have realized that when fitting the random variable as a fixed 
effect in a simple glm, I end up with 0 residual degrees of freedom.



Thanks in advance for your help,

Olga