Regression modelQuasi-experimental / causal inference

Heterogeneous Treatment Effect Propensity Score Matching

Heterogeneous Treatment Effect Propensity Score Matching extends standard PSM to estimate how treatment effects vary across subgroups or individual characteristics. Rather than reporting a single average treatment effect, it uses the matched sample to estimate conditional average treatment effects (CATE), revealing which types of units benefit most or least from a treatment.

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Sources

  1. Athey, S., & Imbens, G. W. (2016). Recursive Partitioning for Heterogeneous Causal Effects. Proceedings of the National Academy of Sciences, 113(27), 7353-7360. DOI: 10.1073/pnas.1510489113
  2. Rosenbaum, P. R., & Rubin, D. B. (1983). The Central Role of the Propensity Score in Observational Studies for Causal Effects. Biometrika, 70(1), 41-55. DOI: 10.1093/biomet/70.1.41

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Referenced by

ScholarGateHeterogeneous Treatment Effect Propensity Score Matching (Heterogeneous Treatment Effect Estimation via Propensity Score Matching). Retrieved 2026-06-04 from https://scholargate.app/en/causal-inference/heterogeneous-treatment-effect-propensity-score-matching