[R-sig-eco] QIC for conditional logistic regression + GEE

[Mathieu Basille]

Dear list,

I'm currently trying to fit a conditional logistic regression on 
correlated data (these are actually steps from animals, with 1 case and 
a bunch of random controls). The state of the art is to use a GEE 
approach to estimate the variance of the coefficients, using a coxph 
model by strata (composed of one step + corresponding random steps), and 
a clustered estimation of the variances (i.e. robust variances). This is 
quite easy to achieve in R, with nevertheless some convergence problems...

The next step, however, is to select the best model within a set of 
competing ones. Again, the state of the art is to use the 
Quasi-likelihood under Independence Criterion (QIC) [1] also sometimes 
known as modified AIC [2].

After an extensive search (with the help of rseek.org), I was unable to 
find any guidance for this criterion using R. I know the criterion is 
already available in SAS or Stata, but I was wondering if anyone tried 
to code QIC in R? That would be a very valuable tool in the R toolbox!

I was considering posting this question directly to the main R-help, but 
decided to try it here first... Let me know if it is the right move!

Sincerely,
Mathieu Basille.


[1] Pan, W. (2001a). Akaike's information criterion in generalized 
estimating equations. Biometrics, 57, 120-125.
http://www.biostat.jhsph.edu/~fdominic/teaching/bio655/references/extra/QIC.biometrics.pdf

[2] McCullagh, P., and Nelder, J. A. (1989). Generalized Linear Models 
(2nd ed.). London:Chapman & Hall.

See an example in: A. H. M. M. Latif, M. Z. Hossain and M. A. Islam: 
Model selection using modified Akaike's Information Criterion: an 
application to maternal morbidity data. Austrian Journal of Statistics, 
37, 2008, 175-184.
http://www.stat.tugraz.at/AJS/ausg082/082Latif.pdf


-- 

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Mathieu Basille, Post-Doc

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Laboratoire d'Écologie Comportementale et de Conservation de la Faune
+ Centre d'Étude de la Forêt
Département de Biologie
Université Laval, Québec

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http://ase-research.org/basille

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