[R] Estimating QAIC using glm with the quasibinomial family

[dgillis at cc.umanitoba.ca]

Hello R-list.  I am a "long time listener - first time caller" who has  
been using R in research and graduate teaching for over 5 years.  I  
hope that my question is simple but not too foolish.  I've looked  
through the FAQ and searched the R site mail list with some close hits  
but no direct answers, so...
I would like to estimate QAIC (and QAICc) for a glm fit using the  
quasibinomial family.  I found a general reference suggesting a simple  
solution:

"we calculated QAICc adjusting for overdispersion by dividing the  
residual deviance (i.e. -2 loglikelihood) with the overdispersion  
parameter calculated from the most complex model as the sum of squares  
Pearson residuals divided by the number of degrees of freedom (Burnham  
& Anderson, 2002). "
- Mystrud et al. 2007. Animal Conservation. 10:77-87.


My question is: Will this calculation be valid with the residual  
deviance returned by the glm() function using the quasibinomial family  
as reported in R?


I thought I should ask to be certain that there is no dispersion  
correction applied to the reported deviance, as encouraged by Burnham  
and Anderson, 2nd ed., 2002 on p.69:

"When data are overdispersed and c > 1, the proper likelihood is log(L)/c".

Regards,  Darren Gillis

Department of Biological Sciences
Faculty of Science
University of Manitoba
Winnipeg, MB
Canada, R3T 2N2