xtgee miscarriage radiation , ///
corr(exch) i(indexno) fam(binom) link(log) eform
Now you are assuming that the risk will eventually become larger than
1.0. This model can thus not be true. The odds ratios have the
advantage of both being easy to interpret and the model can be true.
There have been many discussions on this issue, e.g.:
http://www.stata.com/statalist/archive/2008-01/msg00308.html or
http://www.stata.com/statalist/archive/2007-08/msg00101.html (comparing
risk differences and odds ratios)
Hope this helps,
Maarten
--- Raoul Reulen <[email protected]> wrote:
> I've got a cohort of pregnant females for whom I want to investigate
> the risk of being exposed to radiation on miscarriage. One group has
> been exposed to radiation before their pregnancy the other not. The
> unit of analysis is the pregnancy and the outcome is miscarriage.
> There can be multiple pregnancies in the cohort of the same female. I
> could use logistic regression with a generalized estimating equation
> (GEE) modification to take into account the clustering of pregnancies
> of the same woman, like this:
>
>
>
> . xtlogit miscarriage radiation , pa corr(exch) i(indexno) robust
> eform
>
>
>
> And this would give me Odds Ratios. However, because the outcome is
> common in this cohort (>10%) these odds ratios cannot be interpreted
> as relative risks. I can calculate relative risks by using
> log-binomial regression or a Poisson regression model with a robust
> error variance. These two methods have been described nicely here:
> http://www.ats.ucla.edu/stat/stata/faq/relative_risk.htm
>
> . glm miscarriage radiation, nolog fam(binom) link(log) eform
>
> . glm miscarriage radiation, nolog fam(poisson) link(log) eform
> robust
>
>
>
> However, how do I take into account the clustering of pregnancies of
> the same woman? Can I use GEE with these two models? If so how?
> Thanks.
>
>
>
> Raoul
>
>
> Raoul Reulen
> Cancer Research UK Graduate Training Fellow
> Centre for Childhood Cancer Survivor Studies
> Department of Public Health & Epidemiology
> University of Birmingham
> Birmingham
>
>
> *
> * For searches and help try:
> * http://www.stata.com/support/faqs/res/findit.html
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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*
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