Structural Equation Models for Dealing With Spatial Confounding

DOI10.1080/00031305.2017.1305290OpenAlexW2598701235WikidataQ58146991 ScholiaQ58146991MaRDI QIDQ5882536

Thomas Kneib, Hauke Thaden

Publication date: 17 March 2023

Published in: The American Statistician (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00031305.2017.1305290

zbMATH Keywords

bias reductionpath analysisgeoadditive regressionrecursive SEM

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (13)

Restricted Spatial Regression Methods: Implications for Inference ⋮ Multivariate effect priors in bivariate semiparametric recursive Gaussian models ⋮ Spatial+: A novel approach to spatial confounding ⋮ Discussion on “Spatial+: A novel approach to spatial confounding” by Dupont, Wood, and Augustin ⋮ Discussion on “Spatial+: A novel approach to spatial confounding” by Emiko Dupont, Simon N. Wood, and Nicole H. Augustin ⋮ Discussion on “Spatial+: a novel approach to spatial confounding” by Emiko Dupont, Simon N. Wood, and Nicole H. Augustin ⋮ A Review of Spatial Causal Inference Methods for Environmental and Epidemiological Applications ⋮ A flexible Bayesian nonconfounding spatial model for analysis of dispersed count data ⋮ On the Effects of Spatial Confounding in Hierarchical Models ⋮ Evaluating recent methods to overcome spatial confounding ⋮ Bayesian spatial quantile modeling applied to the incidence of extreme poverty in Lima-Peru ⋮ Mitigating unobserved spatial confounding when estimating the effect of supermarket access on cardiovascular disease deaths ⋮ MSPOCK: alleviating spatial confounding in multivariate disease mapping models

Uses Software

• GMRFLib
• mgcv
• gamair

Cites Work

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• Bayesian structured additive distributional regression with an application to regional income inequality in Germany
• The importance of scale for spatial-confounding bias and precision of spatial regression estimators
• Bayesian image restoration, with two applications in spatial statistics (with discussion)
• Adding Spatially-Correlated Errors Can Mess Up the Fixed Effect You Love
• Regression
• Gaussian Markov Random Fields
• Dimension Reduction and Alleviation of Confounding for Spatial Generalized Linear Mixed Models
• Effects of Residual Smoothing on the Posterior of the Fixed Effects in Disease‐Mapping Models

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