RERANDOMIZATION TO IMPROVE COVARIATE BALANCE IN EXPERIMENTS

• 成果类型: Article
• 署名作者: Morgan, Kari Lock; Rubin, Donald B.
• 署名单位: Duke University; Harvard University
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/12-AOS1008
• 发表日期: 2012
• 页码: 1263-1282
• 关键词: clinical-trials; Causal Inference; restricted randomization; adaptive allocation; matching methods; DESIGN; BIAS; assignment; PURSUIT; science

摘要

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.