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Bayesian Theory and Applications$
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Paul Damien, Petros Dellaportas, Nicholas G. Polson, and David A. Stephens

Print publication date: 2013

Print ISBN-13: 9780199695607

Published to Oxford Scholarship Online: May 2013

DOI: 10.1093/acprof:oso/9780199695607.001.0001

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Subgroup analysis

Subgroup analysis

Chapter:
(p.576) 29 Subgroup analysis
Source:
Bayesian Theory and Applications
Author(s):

Purushottam W Laud

Siva Sivaganesan

Peter MüLler

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199695607.003.0029

Subgroup analysis involves the comparison of treatment efficacies in a clinical trial among subgroups defined by baseline patient characteristics, such as gender and age. Better subgroup analysis techniques can improve the extraction of information from clinical trials and lead to improved clinical trial designs. This chapter presents methods that cast subgroup analysis as a model selection procedure that can also be seen as a decision problem. Bayesian thinking allows one readily to formulate the probability model and to implement inference and decision making. The material presented here can be seen as a framework in which to carry out subgroup analysis rather than a specific instance of it.

Keywords:   Bayesian methods, decision making, model selection, clinical trials

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