Minimize the Use of Minimization with Unequal Allocation

Authors

  • Michael Proschan,

    Corresponding author
    1. Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, 6700A Rockledge Drive, Room 5140, Bethesda, Maryland 20892-7609, U.S.A.
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  • Erica Brittain,

    1. Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, 6700A Rockledge Drive, Room 5140, Bethesda, Maryland 20892-7609, U.S.A.
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  • Lisa Kammerman

    1. Division of Biometrics 3, Office of Biostatistics, Center for Drug Evaluation and Research, Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993, U.S.A.
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email: ProschaM@niaid.nih.gov

Abstract

Summary Minimization as an alternative to randomization is gaining popularity for small clinical trials. In response to critics’ questions about the proper analysis of such a trial, proponents have argued that a rerandomization approach, akin to a permutation test with conventional randomization, can be used. However, they add that this computationally intensive approach is not necessary because its results are very similar to those of a t-test or test of proportions unless the sample size is very small. We show that minimization applied with unequal allocation causes problems that challenge this conventional wisdom.

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