Marginally interpretable spatial logistic regression with bridge processes

Changwoo J. Lee; David B. Dunson

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arXiv · 2412.04744

Marginally interpretable spatial logistic regression with bridge processes

Changwoo J. Lee·David B. Dunson

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Abstract

In including random effects to account for dependent observations, the odds ratio interpretation of logistic regression coefficients is changed from population-averaged to subject-specific. This is unappealing in many applications, motivating a rich literature on methods that maintain the marginal logistic regression structure without random effects, such as generalized estimating equations. However, for spatial data, random effect approaches are appealing in providing a full probabilistic characterization of the data that can be used for prediction. We propose a new class of spatial logistic regression models that maintain both population-averaged and subject-specific interpretations through a novel class of bridge processes for spatial random effects. These processes are shown to have appealing computational and theoretical properties, including a scale mixture of normal representation. The new methodology is illustrated with simulations and an analysis of childhood malaria prevalence data in the Gambia.

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Changwoo J. Lee, David B. Dunson. 2024-12-06. Marginally interpretable spatial logistic regression with bridge processes. https://arxiv.org/abs/2412.04744

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