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From | Lucas Salas <lucassalas@gmail.com> |
To | statalist@hsphsun2.harvard.edu |
Subject | st: Alternatives to clogit using generalised additive models (GAM) |
Date | Tue, 20 Dec 2011 14:51:57 +0100 |
Hi, I am performing a matched case-control analysis in which my outcome is binomial (Cancer yes/no) and my exposure is continuous non-normal. I have already fitted some conditional logistic regression to account for matching using quartiles as boundaries to overcome the non-normality. However, I am interested in explore the dose-response curves and the fitting of my model using a GAM approach. The actual GAM module for Stata is the Fortran app developed by Hastie and Tibshirani, which do not allow any fixed effects adjustment (conditional or unconditional). I have seen these potential alternatives in different webpages: 1. Introducing a match dummy variable in my GAM model. As you could expect my strata are rather sparse so this is not helpful. 2. Fitting a Cox model using exact partial likelihood and using the match as the strata. The logic behind the conditional logistic regression is ok, but I cannot figure out how this applies to a GAM model, and how can I extrapolate this to graph the dose response. 3. Using a vectorial GAM to account for the matching. I have not found any Stata alternative to this procedure. I'd be very grateful for any potential ideas, or if you know any kind of user written ado that might be useful for this data. Thanks, Lucas * * 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/