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Estimation and Prediction in the Presence of Spatial Confounding for Spatial Linear Models

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  • Garritt L. Page
  • Yajun Liu
  • Zhuoqiong He
  • Donchu Sun

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  • Garritt L. Page & Yajun Liu & Zhuoqiong He & Donchu Sun, 2017. "Estimation and Prediction in the Presence of Spatial Confounding for Spatial Linear Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(3), pages 780-797, September.
    • Handle: RePEc:bla:scjsta:v:44:y:2017:i:3:p:780-797
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    File URL: http://hdl.handle.net/10.1111/sjos.12275
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    References listed on IDEAS

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    1. Duncan Lee & Alastair Rushworth & Sujit K. Sahu, 2014. "A Bayesian localized conditional autoregressive model for estimating the health effects of air pollution," Biometrics, The International Biometric Society, vol. 70(2), pages 419-429, June.
    2. Hodges, James S. & Reich, Brian J., 2010. "Adding Spatially-Correlated Errors Can Mess Up the Fixed Effect You Love," The American Statistician, American Statistical Association, vol. 64(4), pages 325-334.
    3. John Hughes & Murali Haran, 2013. "Dimension reduction and alleviation of confounding for spatial generalized linear mixed models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(1), pages 139-159, January.
    4. Brian J. Reich & James S. Hodges & Vesna Zadnik, 2006. "Effects of Residual Smoothing on the Posterior of the Fixed Effects in Disease-Mapping Models," Biometrics, The International Biometric Society, vol. 62(4), pages 1197-1206, December.
    5. Ephraim M. Hanks & Erin M. Schliep & Mevin B. Hooten & Jennifer A. Hoeting, 2015. "Restricted spatial regression in practice: geostatistical models, confounding, and robustness under model misspecification," Environmetrics, John Wiley & Sons, Ltd., vol. 26(4), pages 243-254, June.
    6. Zhuoqiong He & Dongchu Sun, 2000. "Hierarchical Bayes Estimation of Hunting Success Rates with Spatial Correlations," Biometrics, The International Biometric Society, vol. 56(2), pages 360-367, June.
    7. J. Besag & D. Higdon, 1999. "Bayesian analysis of agricultural field experiments," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(4), pages 691-746.
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    Cited by:

    1. Widemberg S. Nobre & Alexandra M. Schmidt & João B. M. Pereira, 2021. "On the Effects of Spatial Confounding in Hierarchical Models," International Statistical Review, International Statistical Institute, vol. 89(2), pages 302-322, August.
    2. Joshua P. Keller & Adam A. Szpiro, 2020. "Selecting a scale for spatial confounding adjustment," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 1121-1143, June.
    3. Jennifer F. Bobb & Maricela F. Cruz & Stephen J. Mooney & Adam Drewnowski & David Arterburn & Andrea J. Cook, 2022. "Accounting for spatial confounding in epidemiological studies with individual‐level exposures: An exposure‐penalized spline approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1271-1293, July.
    4. Isa Marques & Thomas Kneib, 2022. "Discussion on “Spatial+: A novel approach to spatial confounding” by Emiko Dupont, Simon N. Wood, and Nicole H. Augustin," Biometrics, The International Biometric Society, vol. 78(4), pages 1295-1299, December.
    5. Alexandra M. Schmidt, 2022. "Discussion on “Spatial+: a novel approach to spatial confounding” by Emiko Dupont, Simon N. Wood, and Nicole H. Augustin," Biometrics, The International Biometric Society, vol. 78(4), pages 1300-1304, December.
    6. Emiko Dupont & Simon N. Wood & Nicole H. Augustin, 2022. "Spatial+: A novel approach to spatial confounding," Biometrics, The International Biometric Society, vol. 78(4), pages 1279-1290, December.
    7. Brian J. Reich & Shu Yang & Yawen Guan & Andrew B. Giffin & Matthew J. Miller & Ana Rappold, 2021. "A Review of Spatial Causal Inference Methods for Environmental and Epidemiological Applications," International Statistical Review, International Statistical Institute, vol. 89(3), pages 605-634, December.
    8. Isa Marques & Thomas Kneib & Nadja Klein, 2022. "Mitigating spatial confounding by explicitly correlating Gaussian random fields," Environmetrics, John Wiley & Sons, Ltd., vol. 33(5), August.

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