RERANDOMIZATION TO IMPROVE COVARIATE BALANCE IN EXPERIMENTS
RERANDOMIZATION TO IMPROVE COVARIATE BALANCE IN EXPERIMENTS
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DOI：
10.1214/12-aos1008
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发表时间：
2012-04-01
影响因子：
4.5
通讯作者：
Rubin, Donald B.
中科院分区：
文献类型：
--
作者：
Morgan, Kari Lock;Rubin, Donald B.
随机实验是估计因果效应的“黄金标准”，但在实践中，治疗组之间的协变量分布往往存在机会不平衡。如果在单位接受治疗之前协变量数据可用，则可以通过在物理实验进行之前首先检查协变量平衡来减轻这些机会不平衡。如果预先指定了不平衡的精确定义，则可以丢弃不平衡的随机化，然后重新随机化，并且可以继续该过程，直到实现根据定义的随机化产生平衡。通过改善协变量平衡，重新随机化可以提供更精确、更可靠的治疗效果估计。
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.