Improving Effect Estimates by Limiting the Variability in Inverse Propensity Score Weights

Keith Kranker, Laura Blue and Lauren Vollmer Forrow

Mathematica Policy Research Reports from Mathematica Policy Research

Abstract: This study describes a novel method to reweight a comparison group used for causal inference, so the group is similar to a treatment group on observable characteristics yet avoids highly variable weights that would limit statistical power.

Keywords: Causal inference; Covariate balance; Observational studies; Power (search for similar items in EconPapers)
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Journal Article: Improving Effect Estimates by Limiting the Variability in Inverse Propensity Score Weights (2021)
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