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Rejoinder to the discussions of “Spatial+: A novel approach to spatial confounding”

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  • Emiko Dupont
  • Simon N. Wood
  • Nicole H. Augustin

Abstract

In this rejoinder, we set out some of the main points that we took from the discussions of our paper “Spatial+: A novel approach to spatial confounding.” The comments provided by the discussants include excellent questions and suggestions for extensions and improvements to spatial+. The discussions also highlight the growing interest in understanding spatial confounding, underpinned by the many recent contributions to the literature on this topic.

Suggested Citation

  • Emiko Dupont & Simon N. Wood & Nicole H. Augustin, 2022. "Rejoinder to the discussions of “Spatial+: A novel approach to spatial confounding”," Biometrics, The International Biometric Society, vol. 78(4), pages 1309-1312, December.
    • Handle: RePEc:bla:biomet:v:78:y:2022:i:4:p:1309-1312
    DOI: 10.1111/biom.13653
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    References listed on IDEAS

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    1. 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.
    2. 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.
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    Cited by:

    1. Carlos García & Zaida Quiroz & Marcos Prates, 2023. "Bayesian spatial quantile modeling applied to the incidence of extreme poverty in Lima–Peru," Computational Statistics, Springer, vol. 38(2), pages 603-621, June.

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