Covariate Balancing Propensity Score

Princeton University

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Abstract

Summary The propensity score plays a central role in a variety of causal inference settings. In particular, matching and weighting methods based on the estimated propensity score have become increasingly common in the analysis of observational data. Despite their popularity and theoretical appeal, the main practical difficulty of these methods is that the propensity score must be estimated. Researchers have found that slight misspecification of the propensity score model can result in substantial bias of estimated treatment effects. We introduce covariate balancing propensity score (CBPS) methodology, which models treatment assignment while optimizing the covariate balance. The CBPS exploits the dual…

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1,313
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Authors

2

Topics & keywords

Keywords
  • Propensity score matching
  • Covariate
  • Causal inference
  • Statistics
  • Observational study
  • Matching (statistics)
  • Computer science
  • Econometrics
UN Sustainable Development Goals
  • No poverty
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