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Activity Number:
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7
- Bayesian Nonparametrics in Causal Inference
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Type:
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Invited
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Date/Time:
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Sunday, July 29, 2018 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Bayesian Statistical Science
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Abstract #326590
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Presentation
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Title:
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Regularization and Aliasing in the Estimation of Treatment Effect Moderation
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Author(s):
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Paul Richard Hahn* and Carlos Carvalho and Jared S Murray
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Companies:
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Arizona State University and University of Texas and University of Texas at Austin
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Keywords:
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individual treatment effects;
moderation;
causal inference;
confounding;
nonlinear regression;
regularization
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Abstract:
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Nonlinear regression methods can bias estimation of treatment effects when moderating variables are codependent with the response variable in ways not due to treatment. In this case we say that the moderator is aliased with the outcome. We develop a Bayesian approach to mitigate this unintentional bias, particularly for the purpose of disentangling idiosyncratic group level effects from common covariate effects.
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Authors who are presenting talks have a * after their name.
