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Activity Number:
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25
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Type:
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Contributed
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Date/Time:
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Sunday, August 3, 2008 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #301211 |
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Title:
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A Model for Spatio-Temporally Clustered Disease Rates
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Author(s):
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Ronald Gangnon*+
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Companies:
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University of Wisconsin-Madison
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Address:
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603 WARF Office Building, Madison, WI, 53726,
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Keywords:
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breast cancer ; spatial modeling ; temporal modeling ; cluster detection ; Bayes factor
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Abstract:
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We describe an extension of a model for spatial clustering proposed by Gangnon and Clayton (2001) to spatio-temporal data. As in the purely spatial model, a large set of circular regions of varying radii centered at observed locations are considered as potential clusters (e.g., subregions with a different pattern of risk than the remainder of the study region). Within the spatio-temporal model, no specific parametric form is imposed on the temporal pattern of risk within each cluster. In addition to the clusters, the proposed model incorporates spatial and spatio-temporal heterogeneity effects and can readily accommodate regional covariates. Inference is performed in a Bayesian framework using MCMC. We illustrate the approach with an application of the model to data on female breast cancer mortality in Japan.
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