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Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

Modelo Estrutural Marginal Espacial×Ponderação por Escore de Propensão (PEP / IPW)×
ÁreaInferência causalInferência causal
FamíliaRegression modelRegression model
Ano de origem2000s–2010s1983 (propensity score); 2003 (efficient IPW estimator)
Autor originalRobins, Hernan & Brumback (MSM foundation, 2000); spatial extensions developed in spatial epidemiology literatureRosenbaum & Rubin (propensity score); Hirano, Imbens & Ridder (efficient weighting)
TipoCausal inference / spatial weightingCausal inference / reweighting
Fonte seminalRobins, 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 ↗
Outros nomesSpatial MSM, Geospatial MSM, Spatial IPW-MSM, Space-time marginal structural modelPSW, inverse probability weighting, IPW, propensity-based weighting
Relacionados66
ResumoThe 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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ScholarGateComparar métodos: Spatial Marginal Structural Model · Propensity Score Weighting. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare