Jämför metoder
Granska de valda metoderna sida vid sida; rader som skiljer sig är markerade.
| Spatial Marginal Structural Model× | Propensitetspoängsviktning (PSW / IPW)× | |
|---|---|---|
| Ämnesområde | Kausal inferens | Kausal inferens |
| Familj | Regression model | Regression model |
| Ursprungsår≠ | 2000s–2010s | 1983 (propensity score); 2003 (efficient IPW estimator) |
| Upphovsperson≠ | Robins, Hernan & Brumback (MSM foundation, 2000); spatial extensions developed in spatial epidemiology literature | Rosenbaum & Rubin (propensity score); Hirano, Imbens & Ridder (efficient weighting) |
| Typ≠ | Causal inference / spatial weighting | Causal inference / reweighting |
| Ursprungskälla≠ | 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 ↗ |
| Alias | Spatial MSM, Geospatial MSM, Spatial IPW-MSM, Space-time marginal structural model | PSW, inverse probability weighting, IPW, propensity-based weighting |
| Närliggande | 6 | 6 |
| Sammanfattning≠ | 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. | Propensity score weighting is a causal-inference method that reweights observations so that the covariate distributions of treated and untreated units look exchangeable, enabling unbiased estimation of average treatment effects from observational data. Each unit receives a weight that is the inverse of its probability of receiving the treatment it actually received — a strategy formalised by Rosenbaum and Rubin (1983) and given its efficient semiparametric form by Hirano, Imbens and Ridder (2003). |
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