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Regression modelQuasi-experimental / causal inference

Placebo tests for heterogeneous treatment effects

Placebo tests for heterogeneous treatment effects are falsification strategies used to validate whether estimated variation in treatment effects across subgroups or covariate values is genuine rather than an artifact of model specification, overfitting, or coincidental patterns. By applying the same estimation procedure to pseudo-treatments, fake outcomes, or subgroups that logically should not differ, researchers check that observed heterogeneity reflects real causal variation.

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  1. Imbens, G. W., & Rubin, D. B. (2015). Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction. Cambridge University Press. ISBN: 978-0521885881
  2. Athey, S., & Imbens, G. (2016). Recursive partitioning for heterogeneous causal effects. Proceedings of the National Academy of Sciences, 113(27), 7353-7360. DOI: 10.1073/pnas.1510489113

Kā citēt šo lapu

ScholarGate. (2026, June 3). Placebo Test for Heterogeneous Treatment Effects. ScholarGate. https://scholargate.app/lv/causal-inference/heterogeneous-treatment-effect-placebo-test

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Salīdzināt blakus
ScholarGateHeterogeneous treatment effect Placebo test (Placebo Test for Heterogeneous Treatment Effects). Izgūts 2026-06-17 no https://scholargate.app/lv/causal-inference/heterogeneous-treatment-effect-placebo-test · Datu kopa: https://doi.org/10.5281/zenodo.20539026