The Propensity Score with Continuous Treatments
Abstract
of the binary treatment propensity score, which we label the generalized propensity score (GPS). We demonstrate that the GPS has many of the attractive properties of the binary treatment propensity score. Just as in the binary treatment case, adjusting for this scalar function of the covariates removes all biases associated with dierences in the covariates. The GPS also has certain balancing properties that can be used to assess the adequacy of particular specications of the score. We discuss estimation and inference in a parametric
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- Authors
- Hirano, K., & Imbens, G. W.
- Affiliations
- University of Miami (US)
- University of California, Berkeley (US)
- Venue
- Wiley Series in Probability and Statistics
- Publisher
- Wiley
- Published
- 2004-07-23
- Pages
- 73-84
- ISSN
- 1940-6347 (ISSN-L)
- OpenAlex
- W2139529156
- Cited by
- 1,064
- References
- 1
- Citations by year
- 2026: 38 · 2025: 65 · 2024: 99 · 2023: 88 · 2022: 72 · 2021: 83 · 2020: 102 · 2019: 78 · 2018: 61 · 2017: 42 · 2016: 57 · 2015: 39 · 2014: 48 · 2013: 34 · 2012: 53
- Type
- other
- Language
- en
- Open access
- closed
- Locations
- Wiley series in probability and statistics (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- generalized propensity score, continuous treatment, covariate balance, causal inference, treatment effect estimation, parameter estimation
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