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June 2014 Sharp bounds on the variance in randomized experiments
Peter M. Aronow, Donald P. Green, Donald K. K. Lee
Ann. Statist. 42(3): 850-871 (June 2014). DOI: 10.1214/13-AOS1200


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.


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Peter M. Aronow. Donald P. Green. Donald K. K. Lee. "Sharp bounds on the variance in randomized experiments." Ann. Statist. 42 (3) 850 - 871, June 2014.


Published: June 2014
First available in Project Euclid: 20 May 2014

zbMATH: 1305.62024
MathSciNet: MR3210989
Digital Object Identifier: 10.1214/13-AOS1200

Primary: 62A01
Secondary: 62D99 , 62G15

Keywords: Causal inference , finite populations , potential outcomes , randomized experiments , variance estimation

Rights: Copyright © 2014 Institute of Mathematical Statistics


Vol.42 • No. 3 • June 2014
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