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Activity Number:
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511
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 5, 2009 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #305476 |
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Title:
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A Multivariate Spatial Factor Model for Clustered Data with Informatively Present Mixed Responses
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Author(s):
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Dipankar Bandyopadhyay*+ and Brian J. Reich and Jyotika Fernandes
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Companies:
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Medical University of South Carolina and North Carolina State University and Medical University of South Carolina
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Address:
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135 Cannon Street, Suite 303, Charleston, SC, 29425,
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Keywords:
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periodontal ; spatial ; clustered ; multivariate
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Abstract:
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Analyzing periodontal disease data poses several challenges. These spatially-referenced data are a mix of binary and continuous responses, making joint modeling difficult. Also, it is likely that the number and location of missing teeth informs about the subject's oral health. In this talk, we develop a multivariate spatial framework for these data which jointly models the binary and continuous responses as a function of a single latent spatial process representing general oral health. We also use the latent spatial process to model the location of missing teeth. We show using simulated and real data that exploiting spatial associations and jointly modeling the response and measurement location mitigates the problems presented by these informatively present data.
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