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Re: st: analysis of multi-site studies


From   Ricardo Ovaldia <ovaldia@yahoo.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: analysis of multi-site studies
Date   Mon, 1 Nov 2004 05:47:27 -0800 (PST)

Thank you Stas and Constantine.

I have one follow-up question, please. From your
answers I surmise that from all the possible ways
available to adjust for study-site effect, with only 5
OB-GYN clinics, I am better off using -clogit- and not
dummies, nor random effects, nor GEE models. But, how
about logistic regression clustering on study-site, is
that better?

Thank you,
Ricardo.




--- Constantine Daskalakis
<C_Daskalakis@mail.jci.tju.edu> wrote:

> At 12:15 PM 10/29/2004, Ricardo Ovaldia wrote:
> >--- Stas Kolenikov <skolenik@gmail.com> wrote:
> >
> > > Your answer to (2) is not correct: the fixed
> effect
> > > is equivalent to
> > > introducing dummy variables only for the linear
> > > model. For anything
> > > non-linear, the fixed effect is conditioning on
> this
> > > (for the -clogit- > model, you are conditioning
> on >
> >the number of 0's and  1's in each
> > > center), which is some complicated algebra.
> >
> >Thank you Stas. I though that they were equal if
> there
> >was only a single independent categorical variable
> in
> >the model.
> >
> >Then the question remains, am I justified in using
> >-clogit- and not dummies in this situation?
> >
> >Regards,
> >Ricardo.
> 
> I am pretty sure that they are asymptotically
> equivalent, provided that the 
> number of strata (indicator terms for the centers)
> is small compared to the 
> total sample size. Or, to be more precise, that the
> number of observations 
> within each stratum is "large." If not, then the
> unconditional logistic 
> regression with dummies is biased.
> See Breslow & Day (IARC monograph on case-control
> studies) and Hosmer & 
> Lemeshow (Logistic Regression book).
> 
> 
> 
> 
> 
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>
________________________________________________________________
> Constantine Daskalakis, ScD
> Assistant Professor,
> Biostatistics Section, Thomas Jefferson University,
> 211 S. 9th St. #602, Philadelphia, PA 19107
>     Tel: 215-955-5695
>     Fax: 215-503-3804
>     Email: c_daskalakis@mail.jci.tju.edu
>     Webpage:
> http://www.jefferson.edu/medicine/pharmacology/bio/ 
> 
> 
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=====
Ricardo Ovaldia, MS
Statistician 
Oklahoma City, OK


		
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