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Statistical evidence and sample size determination for Bayesian hypothesis testing

✍ Scribed by Fulvio De Santis

Publisher: Elsevier Science
Year: 2004
Tongue: English
Weight: 363 KB
Volume: 124
Category: Article
ISSN: 0378-3758
DOI: 10.1016/s0378-3758(03)00198-8

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✦ Synopsis

This paper considers the problem of choosing the sample size for testing hypotheses on the parameters of a model using Bayes factors. Extending the evidential approach outlined in Royall (Statistical Evidence: a Likelihood paradigm. Chapman & Hall, London (1997), J. Amer. Statist. Assoc. 95 (2000) 760) to the Bayesian framework, the predictive criterion proposed for determining the sample size is maximizing the probability of obtaining substantial evidence in favor of the true hypotheses, i.e. minimizing the probabilities of having either misleading or weak evidence. The method is developed for the normal model in several testing problems that arise, for instance, when comparing treatments in clinical trials.

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