Methoden vergleichen
Prüfen Sie die ausgewählten Methoden nebeneinander; abweichende Zeilen sind hervorgehoben.
| Paneldaten-Modell für marginale Struktur (MSM)× | Paneldaten Inverse Wahrscheinlichkeitsgewichtung× | |
|---|---|---|
| Fachgebiet | Kausale Inferenz | Kausale Inferenz |
| Familie | Regression model | Regression model |
| Entstehungsjahr | 2000 | 2000 |
| Urheber≠ | James M. Robins, Miguel A. Hernan, Babette Brumback | Robins, Hernan & Brumback |
| Typ≠ | Causal model for time-varying treatments | Reweighting / causal inference |
| Wegweisende Quelle | Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560. DOI ↗ | Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560. DOI ↗ |
| Aliasnamen | MSM panel, longitudinal MSM, panel MSM, time-varying treatment MSM | panel IPW, longitudinal IPW, time-varying IPW, panel IPTW |
| Verwandt | 5 | 5 |
| Zusammenfassung≠ | 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. | Panel Data Inverse Probability Weighting (panel IPW) estimates the causal effect of a time-varying treatment by reweighting observed units to create a pseudo-population in which treatment is independent of measured confounders at each time point. It extends the cross-sectional IPW framework to longitudinal settings where treatment status and confounders both evolve across multiple periods. |
| ScholarGateDatensatz ↗ |
|
|