Autoregressive spatial smoothing and temporal spline smoothing for mapping rates.
This article proposes generalized additive mixed models for the analysis of geographic and temporal variability of mortality rates. This class of models accommodates random spatial effects and fixed and random temporal components. Spatiotemporal models that use autoregressive local smoothing across the spatial dimension and B-spline smoothing over the temporal dimension are developed. The objective is the identification of temporal treads and the production of a series of smoothed maps from which spatial patterns of mortality risks can be monitored over time. Regions with consistently high rate estimates may be followed for further investigation. The methodology is illustrated by analysis of British Columbia infant mortality data.
MacNab
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YC
Department of Health Care and Epidemiology, University of British Columbia, and Centre for Community Child Health and Health Evaluation Research, British Columbia Institute for Children's and Women's Health, Vancouver, Canada. ymacnab@interchange.ubc.ca
Dean
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CB
D001699:Biometry; D001955:British Columbia / Q000453:epidemiology; D006801:Humans; D007223:Infant; D007226:Infant Mortality; D007231:Infant, Newborn; D015233:Models, Statistical; D012044:Regression Analysis