Abstract #300928

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JSM 2002 Abstract #300928
Activity Number: 167
Type: Topic Contributed
Date/Time: Tuesday, August 13, 2002 : 8:30 AM to 10:20 AM
Sponsor: ENAR
Abstract - #300928
Title: Cluster Modeling for Disease Rate Mapping
Author(s): Ronald Gangnon*+ and Clayton Murray
Affiliation(s): University of Wisconsin and University of Wisconsin
Address: 610 N. Walnut Street, Madison, Wisconsin, 53705, USA
Keywords: Bayesian methods ; spatial clustering ; disease mapping ; poisson model
Abstract:

We discuss a model for spatial clustering of disease cases applicable to cell count data. In this model, the region of space under study is partitioned into a single large background area and a relatively small number of clusters. Here, a cluster is a geographically small area with higher or lower risk than than background. We adopt a Bayesian framework for inference, using prior specifications of the relative probabilities of various types of clusters to guide, but not necessarily limit, selection from the available models. We describe a randomized agglomerative clustering algorithm for finding models with high posterior probability. We illustrate the use of these modelling techniques through the construction of maps of the 1995 mortality rates from five cancers (breast, cervical, colon, lung, and stomach) in the United States.

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