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Ding, Peng; Dasgupta, Tirthankar – Grantee Submission, 2017
Fisher randomization tests for Neyman's null hypothesis of no average treatment effects are considered in a finite population setting associated with completely randomized experiments with more than two treatments. The consequences of using the F statistic to conduct such a test are examined both theoretically and computationally, and it is argued…
Descriptors: Statistical Analysis, Statistical Inference, Causal Models, Error Patterns
Guanglei Hong; Jonah Deutsch; Heather D. Hill – Grantee Submission, 2015
Conventional methods for mediation analysis generate biased results when the mediator-outcome relationship depends on the treatment condition. This article shows how the ratio-of-mediator-probability weighting (RMPW) method can be used to decompose total effects into natural direct and indirect effects in the presence of treatment-by-mediator…
Descriptors: Weighted Scores, Probability, Statistical Analysis, Interaction