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Abstract Details
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Activity Number:
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100
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Type:
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Invited
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Date/Time:
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Monday, August 1, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #300210 |
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Title:
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Bayesian Methods for Causal Inference on Mediators with Application to Weight Management Clinical Trials
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Author(s):
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Michael Daniels*+ and Jason Roy and Chanmin Kim and Joseph Hogan and Michael Perri
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Companies:
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University of Florida and University of Pennsylvania and University of Florida and Brown University and University of Florida
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Address:
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Department of Statistics, Gainesville, FL, 32611, USA
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Keywords:
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Mediation ;
Sensitivity analysis
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Abstract:
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We propose a nonparametric Bayesian approach to estimate the natural direct and indirect effects of a mediator in the setting of a continuous mediator and a binary response. Several conditional independence assumptions are introduced (with corresponding sensitivity parameters) to make these effects identifiable from the observed data. This approach is used to assess mediation in a recent weight management clinical trial.
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