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The Role of Pairwise Matching in Experimental Design for an Incidence Outcome

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arxiv 2209.00490 v1 pith:ZMQ3HKFM submitted 2022-09-01 stat.ME

Adam Kapelner , Abba M. Krieger , David Azriel This is my paper
classification stat.ME
keywords designdesignserrorincidencematchingmeanmodeloutcome
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We consider the problem of evaluating designs for a two-arm randomized experiment with an incidence (binary) outcome under a nonparametric general response model. Our two main results are that the priori pair matching design of Greevy et al. (2004) is (1) the optimal design as measured by mean squared error among all block designs which includes complete randomization. And (2), this pair-matching design is minimax, i.e. it provides the lowest mean squared error under an adversarial response model. Theoretical results are supported by simulations and clinical trial data.

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