Asymptotic inference of causal effects with observational studies trimmed by the estimated propensity scores

By Shu Yang, Peng Ding. 2018

94 citations recorded by the source corpus.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/96f9e636691f04d3620e682656c4431793f8e43a

How researchers see this paper

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In Statistics and Probability

1. Xinwei Ma
2. Jingshen Wang
3. Shu Yang
4. Sanjog Misra

Citations in the corpus

• Robust Inference Using Inverse Probability Weighting (2018, background): “Crump, Hotz, Imbens and Mitnik (2009) and Yang and Ding (2018) are two exceptions. They consider the probability weight based trimming, as we do in this paper, but both studies assume that the probability weights are already bounded away from zero. With the IPW estimator as a special case, Cattaneo ”
• Propensity Score Weighting for Causal Inference with Clustered Data (2017, background): “, the average causal effects over a subset of population [71, 72, 73], including the average causal effect on the treated.”