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Extending Multilevel Spatial Models to Include Spatially Varying Coefficients

Citation

Janko, Mark; Goel, Varun; & Emch, Michael E. (2019). Extending Multilevel Spatial Models to Include Spatially Varying Coefficients. Health & Place, 60, 102235. PMCID: PMC6903407

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.

URL

http://dx.doi.org/10.1016/j.healthplace.2019.102235

Reference Type

Journal Article

Journal Title

Health & Place

Author(s)

Janko, Mark
Goel, Varun
Emch, Michael E.

Year Published

2019

Volume Number

60

Pages

102235

PMCID

PMC6903407

Reference ID

12634