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From | Maarten buis <maartenbuis@yahoo.co.uk> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: "Separation" issue in clustered/Longitudinal binary data. |
Date | Wed, 22 Dec 2010 08:19:54 +0000 (GMT) |
--- On Wed, 22/12/10, sigontw@uchicago.edu wrote: > I am now working on a longitudinal dataset. The outcome > variable is a binary variable (a patient-reported drug's > side effect) with repeated measures for three waves. Now I > have an intervention (whether the participant received the > drug), and I have used xtgee, xtlogit and xtmelogit to model > the effects of this intervention on the outcome in a few > different ways. However, no matter which method I used, I > always encountered the separation issue. I may be missing something obvious, but don't you need to use the drug in order to experience its side-effects. This is in part a substantive/medical issue, but also a matter of how the data were collected. Even if you could experience the same symptoms without using the drug, I can easily imagine situations where questionnaires redirected respondents who do not use the drug to the next question, so they trivially cannot have reported the side-effects/symptoms, or in register data where these symptoms are defined as side-effects only when the drug is used, etc. If something like that is happening in your data, then it is hard to see how an "effect" of your treatment could have a meaningful substantive interpretation. In that case the problem is no longer "what kind of technique can I use to estimate my effect?" but "what effect do I want to estimate?" Hope this helps, Maarten -------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://www.maartenbuis.nl -------------------------- * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/