An Optimal Sequential Design for Screening Trials

Publication Type

Journal Article

Publication Date

1998

Abstract

Yao, Begg, and Livingston (1996, Biometrics 52, 992-1001) considered the optimal group size for testing a series of potentially therapeutic agents to identify a promising one as soon as possible for given error rates. The number of patients to be tested with each agent was fixed as the group size. We consider a sequential design that allows early acceptance and rejection, and we provide an optimal strategy to minimize the sample sizes (patients) required using Markov decision processes. The minimization is under the constraints of the two types (false positive and false negative) of error probabilities, with the Lagrangian multipliers corresponding to the cost parameters for the two types of errors. Numerical studies indicate that there can be a substantial reduction in the number of patients required.

Discipline

Econometrics | Medicine and Health Sciences

Research Areas

Econometrics

Publication

Biometrics

Volume

54

Issue

1

First Page

243

Last Page

250

ISSN

0006-341X

Identifier

10.2307/2534011

Publisher

Wiley

Additional URL

https://doi.org/10.2307/2534011

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