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Аналіз чутливості гетерогенних ефектів лікування для причинності×Різниця різниць (Diff-in-Diff)×
ГалузьПричинно-наслідковий висновокЕконометрика
РодинаRegression modelRegression model
Рік появи2000s–2010s1994
Автор методуRosenbaum (sensitivity analysis framework); extended to heterogeneous effects by Crump, Imbens, and othersCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
ТипRobustness / sensitivity checkCausal inference / panel regression
Основоположне джерелоRosenbaum, P. R. (2002). Observational Studies (2nd ed.). Springer. ISBN: 978-0387989679Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Інші назвиHTE sensitivity analysis, heterogeneous-effects sensitivity analysis, sensitivity analysis with effect heterogeneity, HTE robustness analysisdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Пов'язані55
ПідсумокHeterogeneous 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.Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes.
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ScholarGateПорівняння методів: Heterogeneous Treatment Effect Sensitivity Analysis for Causality · Difference-in-Differences. Отримано 2026-06-17 з https://scholargate.app/uk/compare