Weighting beyond Horvitz-Thompson in causal inference

Weighting beyond Horvitz-Thompson in causal inference

Neyman Seminar
Oct 5, 2016, 04:00 PM - 05:00 PM | 1011 Evans Hall | Happening As Scheduled
Fan Li, Department of Statistical Science, Duke University
Abstract: Covariate balance is crucial for unconfounded descriptive or causal comparisons. However, lack of balance is common in observational studies. This article considers weighting strategies for balancing covariates. We define a general class of weights---the balancing weights---that balance the weighted distributions of the covariates between treatment groups. These weights incorporate the...