On randomization-based causal inference for matched-pair factorial designs
Jiannan Lu and
Statistics & Probability Letters, 2017, vol. 125, issue C, 99-103
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.
Keywords: Experimental design; Factorial effect; Precision; Potential outcome (search for similar items in EconPapers)
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