Comparer des méthodes
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| Modèle structurel marginal (MSM) pour données de panel× | Modèle à effets fixes pour données de panel× | |
|---|---|---|
| Domaine≠ | Inférence causale | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 2000 | 2014 |
| Auteur d'origine≠ | James M. Robins, Miguel A. Hernan, Babette Brumback | Hsiao (textbook treatment); within transformation of panel data |
| Type≠ | Causal model for time-varying treatments | Panel data regression |
| Source fondatrice≠ | Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560. DOI ↗ | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗ |
| Alias | MSM panel, longitudinal MSM, panel MSM, time-varying treatment MSM | fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli |
| Apparentées | 5 | 5 |
| Résumé≠ | A panel data marginal structural model (MSM) uses inverse probability of treatment weighting (IPTW) across multiple time periods to estimate the causal effect of a time-varying treatment, while appropriately adjusting for time-varying confounders that are themselves affected by prior treatment — a bias source that conventional regression cannot handle. | The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014). |
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