Abstract
In this paper we introduce a fully Bayesian approach to sample size determination in clinical trials. In contrast to the usual Bayesian decision theoretic methodology, which assumes a single decision maker, our approach recognizes the existence of three decision makers, namely: the pharmaceutical company conducting the trial, which decides on its size; the regulator, whose approval is necessary for the drug to be licensed for sale; and the public at large, who determine ultimate usage. Moreover, we model the subsequent usage by plausible assumptions for actual behavior, rather than assuming that it represents decisions which are in some sense optimal.
The results, not surprisingly, show that the optimal sample size depends strongly on the expected benefit from a conclusively favorable outcome, and on the strength of the evidence required by the regulator.
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