[R] Estimating QAIC using glm with the quasibinomial family

From: <dgillis_at_cc.umanitoba.ca>
Date: Tue, 06 May 2008 19:02:48 -0500


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



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