Asymptotic theory of rerandomization in treatment–control experiments Article Swipe

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Xinran Li , Peng Ding , Donald B. Rubin ·

YOU? · · 2018 · Open Access · · DOI: https://doi.org/10.1073/pnas.1808191115 · OA: W2963790414

Significance Rerandomization refers to experimental designs that enforce covariate balance. This paper studies the asymptotic properties of the difference-in-means estimator under rerandomization, based on the randomness of the treatment assignment without imposing any parametric modeling assumptions on the covariates or outcome. The non-Gaussian asymptotic distribution allows for constructing large-sample confidence intervals for the average treatment effect and demonstrates the advantages of rerandomization over complete randomization.