Rerandomization to improve covariate balance in experiments

Kari Lock Morgan, Donald B. Rubin

Research output: Contribution to journalArticlepeer-review

191 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1263-1282
Number of pages20
JournalAnnals of Statistics
Issue number2
StatePublished - Apr 2012

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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