Open Access
April 2012 Rerandomization to improve covariate balance in experiments
Kari Lock Morgan, Donald B. Rubin
Ann. Statist. 40(2): 1263-1282 (April 2012). DOI: 10.1214/12-AOS1008


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.


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Kari Lock Morgan. Donald B. Rubin. "Rerandomization to improve covariate balance in experiments." Ann. Statist. 40 (2) 1263 - 1282, April 2012.


Published: April 2012
First available in Project Euclid: 18 July 2012

zbMATH: 1274.62509
MathSciNet: MR2985950
Digital Object Identifier: 10.1214/12-AOS1008

Primary: 62K99

Keywords: causal effect , clinical trial , Experimental design , Hotelling’s $T^{2}$ , Mahalanobis distance , Randomization , treatment allocation

Rights: Copyright © 2012 Institute of Mathematical Statistics

Vol.40 • No. 2 • April 2012
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