Multiple-objective response-adaptive repeated measurement designs in clinical trials for binary responses

Yuanyuan Liang, Yin Li, Jing Wang, Keumhee C. Carriere

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

A multiple-objective allocation strategy was recently proposed for constructing response-adaptive repeated measurement designs for continuous responses. We extend the allocation strategy to constructing response-adaptive repeated measurement designs for binary responses. The approach with binary responses is quite different from the continuous case, as the information matrix is a function of responses, and it involves nonlinear modeling. To deal with these problems, we first build the design on the basis of success probabilities. Then we illustrate how various models can accommodate carryover effects on the basis of logits of response profiles as well as any correlation structure. Through computer simulations, we find that the allocation strategy developed for continuous responses also works well for binary responses. As expected, design efficiency in terms of mean squared error drops sharply, as more emphasis is placed on increasing treatment benefit than estimation precision. However, we find that it can successfully allocate more patients to better treatment sequences without sacrificing much estimation precision.

Original languageEnglish (US)
Pages (from-to)607-617
Number of pages11
JournalStatistics in Medicine
Volume33
Issue number4
DOIs
StatePublished - Feb 20 2014

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Keywords

  • Binary outcome
  • Multiple-objective allocation strategy
  • Response-adaptive repeated measurement designs

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

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