On randomization-based causal inference for matched-pair factorial designs
Methodology
2017-02-06 v1
Abstract
Under the potential outcomes framework, we introduce matched-pair factorial designs, and propose the matched-pair estimator of the factorial effects. We also calculate the randomization-based covariance matrix of the matched-pair estimator, and provide the "Neymanian" estimator of the covariance matrix.
Cite
@article{arxiv.1702.00888,
title = {On randomization-based causal inference for matched-pair factorial designs},
author = {Jiannan Lu and Alex Deng},
journal= {arXiv preprint arXiv:1702.00888},
year = {2017}
}
Comments
To appear in Statistics & Probability Letters