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Activity Number: 42
Type: Contributed
Date/Time: Sunday, August 9, 2015 : 2:00 PM to 3:50 PM
Sponsor: Biopharmaceutical Section
Abstract #314782 View Presentation
Title: Estimation of Treatment Effect in a Sub-Population: An Empirical Bayes Approach
Author(s): Changyu Shen* and Xiaochun Li and Jaesik Jeong
Companies: Indiana University and Indiana University School of Medicine and Chonnam National University
Keywords: Empirical Bayes ; Heterogeneity in treatment effect ; Sub-group analysis
Abstract:

It is well recognized that the benefit of a medical intervention may not be distributed evenly in the target population due to patient heterogeneity and conclusions based on conventional randomized clinical trials may not apply to every person. Given the increasing cost of randomized trials and difficulties in recruiting patients, there is a strong need to develop analytical approaches to estimate treatment effect in sub-populations. In particular, due to limited sample size for sub-populations and the need for multiple comparisons, standard analysis tends to yield wide confidence intervals of the treatment effect that are often non-informative. We propose an empirical Bayes approach to combine both information embedded in a target sub-population and information from other subjects to construct confidence intervals of the treatment effect. The method is appealing in its simplicity and tangibility in characterizing the uncertainty about the true treatment effect. Simulation studies and a real data analysis are presented.


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