You would have to be careful applying these methods that maximize the
predictive power of the model. You want to make sure that ignorability,
no post-treatment bias, and other assumptions are met. For example, even
if a post-treatment variable is a strong predictor of the outcome, you
would not want to include it since it will biases your inference.
Kosuke
On Mon, 11 Feb 2008, Andrew Stokes wrote:
Hi,
Does anyone have any thoughts on Bayesian Model Averaging as an
approach to estimating a summary treatment effect? Or a different
approach? I would like to incorporate treatment effects obtained
through models from the survival and logit classes and from a variety
of specifications within those classes (both from before and after
matching).
Thanks.
Sincerely,
Andy Stokes
Institute for Health Metrics and Evaluation
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