Sample-size-optimal Bayesian schemes in sequential sampling

dc.contributor.advisor Noel A. C. Cressie Biele, Jonathan
dc.contributor.department Statistics 2018-08-15T06:48:30.000 2020-07-02T06:13:12Z 2020-07-02T06:13:12Z Mon Jan 01 00:00:00 UTC 1990 1990
dc.description.abstract <p>Sequential sampling schemes have traditionally used ad hoc rules for sample size. The variable-sample-size sequential probability ratio test (VPRT), developed by Cressie and Morgan (1986), generalizes the Wald-Wolfowitz one-at-a-time sampling plan. The VPRT finds the sample size that maximizes the expected net gain of sampling, conditional on the accumulated data at hand. In this dissertation, we explore this idea, both theoretically and numerically, using a technique of computation known as backward induction. Applications to sequential testing of means of Gaussian data, and to a sequential procedure of testing efficacy of a pharmaceutical (developed by Berry and Ho, 1988) are presented. The relevance of sampling size optimization to sequential clinical trials is discussed;References. (1) Berry, D. A. and Ho, C-H. 1988. One-Sided Sequential Stopping Boundaries for Clinical Trials: A Decision-Theoretic Approach. Biometrics, 44: 219-227. (2) Cressie, N., and Morgan, P. B. 1986. The VPRT: A Sequential Testing Procedure Dominating the SPRT. Preprint No. 86-17. Statistical Laboratory, Iowa State University, Ames.</p>
dc.format.mimetype application/pdf
dc.identifier archive/
dc.identifier.articleid 10393
dc.identifier.contextkey 6359890
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath rtd/9394
dc.language.iso en
dc.source.bitstream archive/|||Sat Jan 15 02:32:13 UTC 2022
dc.subject.disciplines Statistics and Probability
dc.subject.keywords Statistics
dc.title Sample-size-optimal Bayesian schemes in sequential sampling
dc.type article
dc.type.genre dissertation
dspace.entity.type Publication
relation.isOrgUnitOfPublication 264904d9-9e66-4169-8e11-034e537ddbca dissertation Doctor of Philosophy
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