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Robustā Margilālā Strukturālā Modelēšana×Diferenču starpībām (Diff-in-Diff)×
NozareCēloņsakarību secināšanaEkonometrija
SaimeRegression modelRegression model
Izcelsmes gads2000–20041994
AutorsRobins, Hernán & Brumback; robustness extensions by Scharfstein, Rotnitzky, Lunceford & DavidianCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TipsCausal inference / weighted regressionCausal inference / panel regression
PirmavotsRobins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Citi nosaukumirobust MSM, doubly-robust MSM, sandwich-SE MSM, robust IPTW marginal structural modeldiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Saistītās65
KopsavilkumsRobust Marginal Structural Models (robust MSMs) extend the standard MSM framework — which uses inverse probability of treatment weighting to handle time-varying confounding — by pairing IPTW estimation with sandwich (robust) standard errors or doubly-robust estimators. This combination yields valid causal estimates and reliable inference even when the outcome regression model is mildly misspecified or weights are moderately variable.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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ScholarGateSalīdzināt metodes: Robust Marginal Structural Model · Difference-in-Differences. Izgūts 2026-06-15 no https://scholargate.app/lv/compare