Extending multilevel spatial models to include spatially varying coefficients |
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Institution: | 1. Department of Human Geography and Spatial Planning, Utrecht University, Heidelberglaan 2, 3584 CS, Utrecht, The Netherlands;2. School of Economic, Political and Policy Sciences, University of Texas at Dallas, 800 W. Campbell Rd, Richardson, TX 75080-3021, USA |
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Abstract: | Multilevel models have long been used by health geographers working on questions of space, place, and health. Similarly, health geographers have pursued interests in determining whether or not the effect of an exposure on a health outcome varies spatially. However, relatively little work has sought to use multilevel models to explore spatial variability in the effects of a contextual exposure on a health outcome. Methodologically, extending multilevel models to allow intercepts and slopes to vary spatially is straightforward. The purpose of this paper, therefore, is to show how multilevel spatial models can be extended to include spatially varying covariate effects. We provide an empirical example on the effect of agriculture on malaria risk in children under 5 years of age in the Democratic Republic of Congo. |
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Keywords: | Health/medical geography Spatially-varying coefficients Multilevel models Bayesian statistics Disease ecology |
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