Rerandomization to improve covariate balance in experiments
Abstract
Randomized experiments are the "gold standard" for estimating causal effects, yet often in practice, chance imbalances exist in covariate distributions between treatment groups. If covariate data are available before units are exposed to treatments, these chance imbalances can be mitigated by first checking covariate balance before the physical experiment takes place. Provided a precise definition of imbalance has been specified in advance, unbalanced randomizations can be discarded, followed by a rerandomization, and this process can continue until a randomization yielding balance according to the definition is achieved. By improving covariate balance, rerandomization provides more precise and trustworthy estimates of treatment effects.
Cite
@article{arxiv.1207.5625,
title = {Rerandomization to improve covariate balance in experiments},
author = {Kari Lock Morgan and Donald B. Rubin},
journal= {arXiv preprint arXiv:1207.5625},
year = {2012}
}
Comments
Published in at http://dx.doi.org/10.1214/12-AOS1008 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)