Сравнение методов

	Робастная маргинальная структурная модель	Разность разностей (Difference-in-Differences, DiD)
Область	Причинно-следственный вывод	Эконометрика
Семейство	Regression model	Regression model
Год появления	2000–2004	1994
Автор метода	Robins, Hernán & Brumback; robustness extensions by Scharfstein, Rotnitzky, Lunceford & Davidian	Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
Тип	Causal inference / weighted regression	Causal inference / panel regression
Основополагающий источник	Robins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560.	Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Другие названия	robust MSM, doubly-robust MSM, sandwich-SE MSM, robust IPTW marginal structural model	diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Связанные	6	5
Сводка	Robust 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.