Dear all,
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
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