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| النموذج الهيكلي الهامشي المكاني× | مطابقة درجة الميل المكانية× | |
|---|---|---|
| المجال | الاستدلال السببي | الاستدلال السببي |
| العائلة | Regression model | Regression model |
| سنة النشأة≠ | 2000s–2010s | 2000s |
| صاحب الطريقة≠ | Robins, Hernan & Brumback (MSM foundation, 2000); spatial extensions developed in spatial epidemiology literature | Extension of Rosenbaum & Rubin (1983) PSM to spatial settings; spatial adaptation developed in applied econometrics and epidemiology literature from the 2000s onward |
| النوع≠ | Causal inference / spatial weighting | Quasi-experimental matching estimator |
| المصدر التأسيسي≠ | Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560. DOI ↗ | Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41-55. DOI ↗ |
| الأسماء البديلة | Spatial MSM, Geospatial MSM, Spatial IPW-MSM, Space-time marginal structural model | Spatial PSM, Geospatial PSM, Spatially-adjusted propensity score matching, Geographic propensity score matching |
| ذات صلة | 6 | 6 |
| الملخص≠ | The Spatial Marginal Structural Model (Spatial MSM) extends the classical marginal structural model to settings where units are geographically distributed and spatial dependencies — such as neighborhood spillovers, clustering, and spatial confounding — may bias causal estimates. It estimates causal effects of spatially varying exposures by constructing inverse probability weights that account for both individual covariates and spatial location, then fitting a weighted outcome model in the resulting pseudo-population. | Spatial Propensity Score Matching (Spatial PSM) extends the classic propensity score matching framework to settings where units are embedded in geographic space and treatment assignment or outcomes may be spatially correlated. By incorporating spatial covariates and adjacency structure into the propensity model and matching procedure, it produces causal estimates that account for geographic confounding and spillover effects. |
| ScholarGateمجموعة البيانات ↗ |
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