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

[Mathieu Basille]

Dear Maarten,

Thank you for the links! They are very useful!

However, in both cases, they address the problem of QIC for GLMs, i.e. 
for parametric models. This said, I was unable to adjust the code for 
Cox models, which are semi-parametric, and use partial likelihood 
instead (which should behave similarly). In the end, I have no idea how 
to extract/compute the quasi partial likelihood for such a model, which 
is required for the QIC...

I'm still struggling a lot about QIC on coxph, any additional hint would 
be greatly appreciated!
Mathieu.


Le 10/11/2010 02:32, Maarten de Groot a écrit :
> Dear Matthieu,
>
> Henric Nilsson
> (http://hisdu.sph.uq.edu.au/lsu/SSAI%20course/course_tools.htm) and
> Casper Kraan
> (http://www.waddenacademie.knaw.nl/fileadmin/inhoud/pdf/06-wadweten/Proefschriften/Thesis_Casper_Kraan.pdf)
> provide the R code for the QIC. Maybe this might be useful to you.
> Interestingly however is that the code of Nilsson gives another QIC
> output as you get from the "yags package.
>
> Kind regards,
>
> Maarten
>
> On 11/9/2010 4:50 PM, Mathieu Basille wrote:
>> Dear Timothy,
>>
>> Thanks for the hint! I didn't know about the package "yags"... I was
>> able to install it and use it in simple cases (glm), and it does
>> provide a QIC!
>>
>> However, it seems to be limited to the case of GLM (any family), but
>> not Cox models... At least, I was unable to use it with a Cox model
>> approach.
>>
>> Last but not least, the routine that computes the QIC (pan.aic) is in
>> C, not in R, and my skills in C are below zero.
>>
>> Any idea?
>> Mathieu.
>>
>>
>> PS: I cc-ed back the list, since it could be useful there...
>>
>>
>>
>>
>> Le 09/11/2010 05:04, treid a écrit :
>>> Hi Mathieu,
>>> Someone has probably already told you, but just in case, there is an R
>>> package named yags that does QIC. Last I looked, you had to go to the
>>> R-forge site to get it rather than cran.
>>> tim.
>>>
>>> ----- Original Message -----
>>> From: Mathieu Basille <basille at ase-research.org>
>>> Date: Monday, November 8, 2010 16:32
>>> Subject: [R-sig-eco] QIC for conditional logistic regression + GEE
>>> To: r-sig-ecology at r-project.org
>>>
>>> > 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
>>> >
>>> >
>>> > --
>>> >
>>> > ~$ whoami
>>> > Mathieu Basille, Post-Doc
>>> >
>>> > ~$ locate
>>> > Laboratoire d'Écologie Comportementale et de Conservation de la Faune
>>> > + Centre d'Étude de la Forêt
>>> > Département de Biologie
>>> > Université Laval, Québec
>>> >
>>> > ~$ info
>>> > http://ase-research.org/basille
>>> >
>>> > ~$ fortune
>>> > ``If you can't win by reason, go for volume.''
>>> > Calvin, by Bill Watterson.
>>> >
>>> > _______________________________________________
>>> > R-sig-ecology mailing list
>>> > R-sig-ecology at r-project.org
>>> > https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
>>
>
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-- 

~$ whoami
Mathieu Basille, Post-Doc

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

~$ info
http://ase-research.org/basille

~$ fortune
``If you can't win by reason, go for volume.''
Calvin, by Bill Watterson.