We propose a Bayesian formulation of the sample size problem for planning clinical trials. The frequentist paradigm for calculating sample sizes for clinical trials is to prespecify the type I and II error probabilities. These error probabilities are conditional on the true hypotheses. Instead we propose prespecifying posterior probabilities which are conditional on the outcome of the trial. Our method is easy to implement and has intuitive interpretations. We illustrate an application of our method to the planning of cancer clinical trials for the Eastern Cooperative Oncology Group (ECOG).
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Lee et al. (2000) studied this question.
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