SHARP BOUNDS ON THE VARIANCE IN RANDOMIZED EXPERIMENTS

• 成果类型: Article
• 署名作者: Aronow, Peter M.; Green, Donald P.; Lee, Donald K. K.
• 署名单位: Yale University; Columbia University; Yale University
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/13-AOS1200
• 发表日期: 2014
• 页码: 850-871
• 关键词: REGRESSION ADJUSTMENTS; inference; DESIGN

摘要

We propose a consistent estimator of sharp bounds on the variance of the difference-in-means estimator in completely randomized experiments. Generalizing Robins [Stat. Med. 7 (1988) 773-785], our results resolve a well-known identification problem in causal inference posed by Neyman [Statist. Sci. 5 (1990) 465-472. Reprint of the original 1923 paper]. A practical implication of our results is that the upper bound estimator facilitates the asymptotically narrowest conservative Wald-type confidence intervals, with applications in randomized controlled and clinical trials.