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On an Approach to Bayesian Sample Sizing in Clinical Trials
This paper explores an approach to Bayesian sample size determination in clinical trials. The approach falls into the category of what is often called “proper Bayesian”, in that it does not mix frequentist concepts with Bayesian ones. A criterion for a “successful trial” is defined in terms of a posterior probability, its probability is assessed using the marginal distribution of the data, and this probability forms the basis for choosing sample sizes. We illustrate with a standard problem in clinical trials, that of establishing superiority of a new drug over a control.
First available in Project Euclid: 23 September 2013
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Mathematical Reviews number (MathSciNet)
Zentralblatt MATH identifier
Primary: 62F15: Bayesian inference 62K99: None of the above, but in this section
Secondary: 62P10: Applications to biology and medical sciences
Copyright © 2013, Institute of Mathematical Statistics
Muirhead, Robb J.; Şoaita, Adina I. On an Approach to Bayesian Sample Sizing in Clinical Trials. Advances in Modern Statistical Theory and Applications: A Festschrift in honor of Morris L. Eaton, 126--137, Institute of Mathematical Statistics, Beachwood, Ohio, USA, 2013. doi:10.1214/12-IMSCOLL1007. https://projecteuclid.org/euclid.imsc/1379942051
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