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A P-spline ANOVA type model in space-time disease mapping
Authors:M D Ugarte  T Goicoa  J Etxeberria  A F Militino
Institution:1. Department of Statistics and O.R, Public University of Navarre, Pamplona, Spain
2. CIBER of Epidemiology and Public Health (CIBERESP), Pamplona, Spain
Abstract:One of the main objectives in disease mapping is the identification of temporal trends and the production of a series of smoothed maps from which spatial patterns of mortality risks can be monitored over time. When studying rare diseases, conditional autoregressive models have been commonly used for smoothing risks. In this work, a P-spline ANOVA type model is used instead. The model is anisotropic and explicitly considers different smooth terms for space, time, and space-time interaction avoiding, in addition, model identifiability problems. The mean squared error of the log-risk predictor is derived accounting for the variability associated to the estimation of the smoothing parameters. The procedure is illustrated analyzing Spanish prostate cancer mortality data in the period 1975–2008.
Keywords:
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