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st: Alternatives to clogit using generalised additive models (GAM)


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
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