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Article: A Bayesian dynamic spatio-temporal interaction model: an application to prostate cancer incidence.(Report)
- Article from:
- Geographical Analysis
- Article date:
- January 1, 2008
- Author:
CopyrightCOPYRIGHT 2008 Ohio State University Press. This material is published under license from the publisher through the Gale Group, Farmington Hills, Michigan. All inquiries regarding rights should be directed to the Gale Group. (Hide copyright information)
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During the past three decades, prostate cancer incidence has changed substantially in the United States. A fully Bayesian hierarchical spatio-temporal interaction model is proposed to estimate prostate cancer incidence rates in the state of Iowa. We introduce random spatial effects to capture the local dependence among regions, random temporal effects to explain the nonlinearity of rates over time, and random spatio-temporal interactions. In addition, we introduce fixed age effects because most epidemiologic data are strongly related to age. We find that prostate cancer incidence in Iowa counties increased sharply over age while incidence rates increased initially, then ...