A Curtailed Procedure for Selecting Among Treatments With Two Bernoulli Endpoints

Elena M. Buzaianu, Pinyuen Chen, Lifang Hsu

Research output: Contribution to journalArticlepeer-review

Abstract

This paper is concerned with a closed adaptive sequential procedure for selecting a random-size subset containing experimental treatments that are better than a standard. All the k treatments under considerations are measured by two endpoints accounting for treatment efficacy and treatment safety respectively. The selection is made with regard to the two binary endpoints. An experimental treatment is considered to be better than the standard if its both endpoints have successful rates higher than the standard ones. We provide a step-by-step sampling rule, stopping rule, and decision rule for the proposed procedure. We show that the proposed sequential procedure achieves the same requirements for the probability of a correct selection as does the fixed-sample-size procedure, but requires fewer observations. We use simulations to evaluate the sample size savings of the proposed procedure over the corresponding fixed-sample-size procedure.

Original languageEnglish (US)
JournalSankhya B
DOIs
StateAccepted/In press - 2021

Keywords

  • 60G40; 62F07; 62L05
  • Curtailment
  • Sample size
  • Subset selection
  • Two binary endpoints

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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