The sample size for a clinical trial: A Bayesian–decision theoretic approach | Zendy

Halpern Jerry | Zendy; Brown Byron Wm. | Zendy; Hornberger John | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Premium

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.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here

Accelerating Research