From thomas@biostat.washington.edu  Tue Feb  3 16:56:22 1998
From: thomas@biostat.washington.edu (Thomas Lumley)
Date: Tue, 3 Feb 1998 08:56:22 -0800 (PST)
Subject: glm(.) / summary.glm(.); [over]dispersion and returning AIC..
In-Reply-To: <199802031049.LAA00411@sophie.ethz.ch>
Message-ID: <Pine.SUN.3.95.980203085427.9015D-100000@chekov>

On Tue, 3 Feb 1998, Martin Maechler wrote:

> I have been implementing a proposal of Jim Lindsey for  glm(.)
> to return AIC values, and
> print.glm(.) and print.summary.glm(.)  printing them....
> however:
<snip>
> 
> For binomial and poisson,
> there are even three possibilities:
> 	
> 	1. no dispersion (as by the proper GLM)
> 	2. overdispersion estimated by the deviance (ratio)
> 	3. overdispersion specified by the user
> 

How about overdispersion as estimated by the mean squared Pearson
residual. Unlike the deviance estimate this works for quasilikelihood (ie
when only first two moments are specified correctly), at least according
to McCullagh & Nelder.


Thomas Lumley
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glm(.) / summary.glm(.); [over]dispersion and returning AIC..
Thomas Lumley