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The sample size for a clinical trial: A Bayesian–decision theoretic approach
Author(s) -
Halpern Jerry,
Brown Byron Wm.,
Hornberger John
Publication year - 2001
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.703
Subject(s) - bayesian probability , sample size determination , computer science , decision theory , sample (material) , statistics , machine learning , artificial intelligence , econometrics , mathematics , chemistry , chromatography
Using decision theory, what is an appropriate sample size for a clinical trial, with a binary endpoint? We present a program, suitable for actual planning, which, with some extensions, implements Canner's solution to this question. Examples with a discussion are given. Implications of a Bayesian approach are discussed. Bayesian and Neyman–Pearson approaches are compared. Copyright © 2001 John Wiley & Sons, Ltd.