Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1151454 | Statistics & Probability Letters | 2016 | 10 Pages |
Abstract
We develop finite-population asymptotic theory for covariate adjustment in randomization-based causal inference for 2K 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.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Jiannan Lu,