JSM 2005 Online Program

Abstract #303392

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	102
Type:	Contributed
Date/Time:	Monday, August 8, 2005 : 8:30 AM to 10:20 AM
Sponsor:	Section on Bayesian Statistical Science
Abstract - #303392
Title:	Bayesian Sensitivity Analyses of Confounded Treatment Effects
Author(s):	Xuemei Wang*+ and Peter F. Thall
Companies:	The University of Texas M. D. Anderson Cancer Center and The University of Texas M. D. Anderson Cancer Center
Address:	1515 Holcombe Unit 447, Houston, TX, 77030, United States
Keywords:	Bayesian sensitivity analysis ; confounded effects ; clinical trials
Abstract:	The primary goal of a randomized clinical trial of two treatments A and B is to compare their effects on the therapeutic outcome in the medical setting. Scientists routinely base such comparisons on the A-versus-B treatment effect. When patients are not randomized between A and B, but treated in single-arm trials of A or B, standard statistical estimators may be scientifically invalid and substantively misleading. It is common practice throughout the medical literature to base statistical comparisons on data from nonrandomized experiments while ignoring confounding trial effects. Many scientists believe the use of regression methods or subset analyses to account for patient covariates when making such comparisons provides a valid estimate. In this talk, we show substantial between-trial effects may persist after accounting for known covariates. We then illustrate Bayesian methods for assessing what the possible distribution of the treatment effect may be.

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