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A sample-size-optimal Bayesian procedure for sequential pharmaceutical trials. (English) Zbl 0822.62091
Summary: Consider a pharmaceutical trial where the consequences of different decisions are expressed on a financial scale. The efficacy of the new drug under consideration has a prior distribution obtained from the underlying biological process, animal experiments, clinical experience, and so forth. {\it D. A. Berry} and {\it C.-H. Ho} [Biometrics 44, No. 1, 219-227 (1988; Zbl 0707.62263)] show how these components are used to establish an optimal (Bayes) sequential testing procedure, assuming a known constant sample size at each decision point. We show how it is also possible to optimize further, with respect to the sample-size rule. This last component of the design, which is missing from most sequential procedures, has the potential to yield considerably larger expected net gains (equivalently, considerably smaller Bayes risks).

62P10Applications of statistics to biology and medical sciences
62L10Sequential statistical analysis
62F15Bayesian inference
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