[R-sig-ME] single argument anova for GLMMs not yet implemented
Douglas Bates
bates at stat.wisc.edu
Thu Dec 11 21:58:39 CET 2008
On Thu, Dec 11, 2008 at 2:52 PM, Andrew Robinson
<A.Robinson at ms.unimelb.edu.au> wrote:
> Echoing Murray's points here - nicely put, Murray - it seems to me
> that the quasi-likelihood and the GLMM are different approaches to the
> same problem.
I agree and I also appreciate Murray's elegant explanation.
> Can anyone provide a substantial example where random effects and
> quasilikelihood have both been necessary?
I'm kind of waiting for Ben Bolker to let us know how things look from
his perspective. I seem to remember that Ben and others in ecological
fields were concerned about overdispersion, even after incorporating
random effects.
>
> Best wishes,
>
> Andrew
>
>
> On Fri, Dec 12, 2008 at 09:11:39AM +1300, Murray Jorgensen wrote:
>> The following is how I think about this at the moment:
>>
>> The quasi-likelihood approach is an attempt at a model-free approach to
>> the problem of overdispersion in non-Gaussian regression situations
>> where standard distributional assumptions fail to provide the observed
>> mean-variance relationship.
>>
>> The glmm approach, on the other hand, does not abandon models and
>> likelihood but seeks to account for the observed mean-variance
>> relationship by adding unobserved latent variables (random effects) to
>> the model.
>>
>> Seeking to combine the two approaches by using both quasilikelihood
>> *and* random effects would seem to be asking for trouble as being able
>> to use two tools on one problem would give a lot of flexibility to the
>> parameter estimation; probably leading to a very flat quasilikelihood
>> surface and ill-determined optima.
>>
>> But all of the above is only thoughts without the benefit of either
>> serious attempts at fitting real data or doing serious theory so I will
>> defer to anyone who has done either!
>>
>> Philosophically, at least, there seems to be clash between the two
>> approaches and I doubt that attempts to combine them will be successful.
>>
>> Murray Jorgensen
>>
>>
>
> --
> Andrew Robinson
> Department of Mathematics and Statistics Tel: +61-3-8344-6410
> University of Melbourne, VIC 3010 Australia Fax: +61-3-8344-4599
> http://www.ms.unimelb.edu.au/~andrewpr
> http://blogs.mbs.edu/fishing-in-the-bay/
>
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