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A Bayesian decision-theoretic model of sequential experimentation with delayed response

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JournalJOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
DateAccepted/In press - 16 Nov 2016
DateE-pub ahead of print - 9 Jan 2017
DatePublished (current) - 30 Oct 2017
Issue number5
Volume79
Number of pages24
Pages (from-to)1439-1462
Early online date9/01/17
Original languageEnglish

Abstract

We propose a Bayesian decision theoretic model of a fully sequential experiment in which the real-valued primary end point is observed with delay. The goal is to identify the sequential experiment which maximizes the expected benefits of technology adoption decisions, minus sampling costs. The solution yields a unified policy defining the optimal ‘do not experiment’–‘fixed sample size experiment’–‘sequential experiment’ regions and optimal stopping boundaries for sequential sampling, as a function of the prior mean benefit and the size of the delay. We apply the model to the field of medical statistics, using data from published clinical trials.

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© Wiley, 2017. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details

    Research areas

  • Bayesian inference, Clinical trials, Delayed observations, Health economics, Sequential experimentation

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