विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| नीति मूल्यांकन सीमांत संरचनात्मक मॉडल× | मार्जिनल स्ट्रक्चरल मॉडल (MSM)× | |
|---|---|---|
| क्षेत्र | कारणात्मक अनुमान | कारणात्मक अनुमान |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष | 2000 | 2000 |
| प्रवर्तक | James M. Robins, Miguel A. Hernan, Babette Brumback | James M. Robins, Miguel A. Hernan, Babette Brumback |
| प्रकार≠ | Causal inference / weighted regression | Causal model / semiparametric weighting |
| मौलिक स्रोत≠ | 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 ↗ |
| उपनाम | MSM for policy evaluation, policy MSM, causal MSM, structural policy weighting model | MSM, MSM-IPTW, marginal structural Cox model, weighted structural model |
| संबंधित≠ | 6 | 5 |
| सारांश≠ | A Policy Evaluation Marginal Structural Model (MSM) is a causal inference framework that estimates the population-average effect of a policy by using inverse probability weighting to create a pseudo-population in which treatment assignment is independent of measured confounders, enabling unbiased comparison of potential outcomes under different policy scenarios from observational data. | A marginal structural model is a causal modeling framework designed to estimate the effect of a time-varying treatment in the presence of time-varying confounders that are themselves affected by prior treatment. By reweighting observations with inverse probability of treatment weights, MSMs create a pseudo-population in which confounding is eliminated, enabling unbiased estimation of causal treatment contrasts even when standard regression adjustments would fail. |
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