Asymptotic theory of rerandomization in treatment-control experiments.

ABSTRACT: Although complete randomization ensures covariate balance on average, the chance of observing significant differences between treatment and control covariate distributions increases with many covariates. Rerandomization discards randomizations that do not satisfy a predetermined covariate balance criterion, generally resulting in better covariate balance and more precise estimates of causal effects. Previous theory has derived finite sample theory for rerandomization under the assumptions of equal treatment group sizes, Gaussian covariate and outcome distributions, or additive causal effects, but not for the general sampling distribution of the difference-in-means estimator for the average causal effect. We develop asymptotic theory for rerandomization without these assumptions, which reve

SUBMITTER: Li X 

PROVIDER: S-EPMC6140533 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature