Chick, Stephen, Forster, Martin orcid.org/0000-0001-8598-9062 and Pertile, Paolo (2017) A Bayesian decision-theoretic model of sequential experimentation with delayed response. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY. pp. 1439-1462. ISSN 1369-7412
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 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 |
Keywords: | Bayesian inference,Clinical trials,Delayed observations,Health economics,Sequential experimentation |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Social Sciences (York) > Economics and Related Studies (York) |
Depositing User: | Pure (York) |
Date Deposited: | 18 Jan 2017 11:57 |
Last Modified: | 08 Mar 2025 00:05 |
Published Version: | https://doi.org/10.1111/rssb.12225 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1111/rssb.12225 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:110768 |