The role of pairwise matching in experimental design for an incidence outcome

Pub Date : 2023-11-27 DOI:10.1111/anzs.12403
Adam Kapelner, Abba M. Krieger, David Azriel
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引用次数: 1

Abstract

We consider the problem of evaluating designs for a two-arm randomised experiment with an incidence (binary) outcome under a non-parametric general response model. Our two main results are that the a priori pair matching design is (1) the optimal design as measured by mean squared error among all block designs which includes complete randomisation. And (2), this pair-matching design is minimax, that is, it provides the lowest mean squared error under an adversarial response model. Theoretical results are supported by simulations and clinical trial data where we demonstrate the superior performance of pairwise matching designs under realistic conditions.
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成对匹配在实验设计中对发生率结果的作用
我们考虑在非参数一般反应模型下评估具有发生率(二元)结果的双臂随机实验设计的问题。我们的两个主要结果是,先验配对设计是(1)在包括完全随机化的所有块设计中,以均方误差衡量的最佳设计。(2)这种配对设计是minimax的,即在对抗响应模型下,它提供了最小的均方误差。理论结果得到了模拟和临床试验数据的支持,在这些数据中,我们证明了在现实条件下成对匹配设计的优越性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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