Bayesian minimum sample size designs for the bernoulli selection problem

Jones, Peter W.; Madhi, Saad Abed

doi:10.1080/07474948808836139

Sequential Analysis

1988

DOI: 10.1080/07474948808836139

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Bayesian minimum sample size designs for the bernoulli selection problem

Peter W. Jones

Saad Abed Madhi

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1991

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Sequential allocation in clinical trials

Wang

1991

Communications in Statistics - Theory and Methods

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Suppose two treatments with binary responses are available for patients with some disease and that each patient will receive one of the two treatments. In this paper we consider the interests of patients both within and outside a trial using a Bayesian bandit approach and conclude that equal allocation is not appropriate for either group of patients. It is suggested that Gittins indices should be used ( using an approach called dynamic discounting by choosing the discount rate based on the number of future patients in the trial) if the disease is rare, and the least failures rule if the disease is common. Some analytical and simulation results are provided.

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Sequential allocation in clinical trials

Wang

1991

Communications in Statistics - Theory and Methods

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show abstract

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Bayesian minimum sample size designs for the bernoulli selection problem

Cited by 1 publication

References 10 publications

Sequential allocation in clinical trials

Sequential allocation in clinical trials

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