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Regression modelQuasi-experimental / causal inference

Rumlig Marginal Strukturel Model

Den Rumrlige Marginale Strukturelle Model (Spatial MSM) udvider den klassiske marginale strukturelle model til situationer, hvor enheder er geografisk fordelt, og rumlige afhængigheder — såsom nabospredning, klyngedannelse og rumlig konfundering — kan forvride kausale estimater. Den estimerer kausale effekter af rumligt varierende eksponeringer ved at konstruere inverse sandsynlighedsvægte, der tager højde for både individuelle kovariater og rumlig placering, og derefter tilpasse en vægtet resultatmodel i den resulterende pseudo-population.

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  1. Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560. DOI: 10.1097/00001648-200009000-00011
  2. Schnell, P. M., & Papadogeorgou, G. (2020). Mitigating unobserved spatial confounding when estimating the effect of supermarket access on cardiovascular disease deaths. Annals of Applied Statistics, 14(2), 793-816. DOI: 10.1214/20-aoas1377

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ScholarGate. (2026, June 3). Spatial Marginal Structural Model with Inverse Probability Weighting. ScholarGate. https://scholargate.app/da/causal-inference/spatial-marginal-structural-model

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ScholarGateSpatial Marginal Structural Model (Spatial Marginal Structural Model with Inverse Probability Weighting). Hentet 2026-06-15 fra https://scholargate.app/da/causal-inference/spatial-marginal-structural-model · Datasæt: https://doi.org/10.5281/zenodo.20539026