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Multiple‐objective response‐adaptive repeated measurement designs in clinical trials for binary responses
Author(s) -
Liang Yuanyuan,
Li Yin,
Wang Jing,
Carriere Keumhee C.
Publication year - 2013
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.5951
Subject(s) - binary number , computer science , basis (linear algebra) , binary data , function (biology) , mathematical optimization , algorithm , mathematics , geometry , arithmetic , evolutionary biology , biology
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. Copyright © 2013 John Wiley & Sons, Ltd.