期刊
STATISTICS & PROBABILITY LETTERS
卷 119, 期 -, 页码 11-20出版社
ELSEVIER
DOI: 10.1016/j.spl.2016.07.010
关键词
Potential outcome; Variance reduction; Finite-population asymptotics
We develop finite-population asymptotic theory for covariate adjustment in randomization-based causal inference for 2(K) factorial designs. In particular, we confirm that both the unadjusted and the covariate-adjusted estimators of the factorial effects are asymptotically unbiased and normal, and the latter is more precise than the former. (C) 2016 Elsevier B.V. All rights reserved.
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