Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Model Structural Marginal pentru Evaluarea Politicilor× | Evaluarea Contrafactuală a Impactului (CIE)× | |
|---|---|---|
| Domeniu | Inferență cauzală | Inferență cauzală |
| Familie | Regression model | Regression model |
| Anul apariției≠ | 2000 | 1970s–2000s |
| Autorul original≠ | James M. Robins, Miguel A. Hernan, Babette Brumback | Heckman, Imbens, Rubin, and the program evaluation literature |
| Tip≠ | Causal inference / weighted regression | Causal inference / program evaluation |
| Sursa seminală≠ | Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550–560. DOI ↗ | Heckman, J. J., & Vytlacil, E. J. (2007). Econometric evaluation of social programs, Part I: Causal models, structural models and econometric policy evaluation. Handbook of Econometrics, 6B, 4779-4874. DOI ↗ |
| Denumiri alternative | MSM for policy evaluation, policy MSM, causal MSM, structural policy weighting model | CIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluation |
| Înrudite≠ | 6 | 5 |
| Rezumat≠ | 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. | Counterfactual Impact Evaluation is a family of causal methods that estimates the effect of an intervention by comparing what actually happened to participants with what would have happened had the intervention not taken place. Formalised in the Rubin Causal Model and extended by Heckman, Imbens and others, CIE underlies most modern program and policy evaluation practice. |
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