Optimality of Matched-Pair Designs in Randomized Controlled Trials

• 成果类型: Article
• 署名作者: Bai, Y. U. E. H. A. O.
• 署名单位: University of Michigan System; University of Michigan
• 刊物名称: AMERICAN ECONOMIC REVIEW
• ISSN/ISSBN: 0002-8282
• DOI: 10.1257/aer.20201856
• 发表日期: 2022
• 页码: 3911-3940
• 关键词: selection; balance; RERANDOMIZATION; regression; IMPACT

摘要

In randomized controlled trials, treatment is often assigned by strat-ified randomization. I show that among all stratified randomiza-tion schemes that treat all units with probability one half, a certain matched-pair design achieves the maximum statistical precision for estimating the average treatment effect. In an important special case, the optimal design pairs units according to the baseline outcome. In a simulation study based on datasets from ten randomized controlled trials, this design lowers the standard error for the estimator of the average treatment effect by 10 percent on average, and by up to 34 percent, relative to the original designs. (JEL C13, C21)