Regression modelQuasi-experimental / causal inference

Heterogeneous Treatment Effect Sensitivity Analysis for Causality

Heterogeneous Treatment Effect Sensitivity Analysis examines how robust subgroup-specific causal estimates are to unobserved confounding. Rather than testing a single average treatment effect, it asks whether the estimated variation in treatment effects across units or subgroups could be explained away by hidden bias, and at what level of hidden bias the causal conclusions for each subgroup would break down.

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Sources

  1. Rosenbaum, P. R. (2002). Observational Studies (2nd ed.). Springer. ISBN: 978-0387989679
  2. Crump, R. K., Hotz, V. J., Imbens, G. W., & Mitnik, O. A. (2008). Nonparametric tests for treatment effect heterogeneity. Review of Economics and Statistics, 90(3), 389-405. DOI: 10.1162/rest.90.3.389

Related methods

ScholarGateHeterogeneous Treatment Effect Sensitivity Analysis for Causality (Sensitivity Analysis for Causality under Heterogeneous Treatment Effects). Retrieved 2026-06-04 from https://scholargate.app/en/causal-inference/heterogeneous-treatment-effect-sensitivity-analysis-for-causality