This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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29
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Type:
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Contributed
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Date/Time:
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Sunday, August 1, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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Abstract - #308469 |
Title:
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Skew-Elliptical Spatial Random-Effect Modeling for Areal Data with Application to Mapping Health Utilization Rates
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Author(s):
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Farouk Salim Nathoo*+ and Pulak Ghosh
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Companies:
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University of Victoria and Indian Institute of Management, Bangalore
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Address:
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Mathematics and Statistics, University of Victoria, Victoria, BC, V8W3R4, Canada
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Keywords:
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areal data ;
conditional autoregressive model ;
Dirichelet process mixture ;
spatial random effects ;
skew-elliptical distribution ;
disease mapping
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Abstract:
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Mixed regression models incorporating spatially correlated random effects are often used for the analysis of small area health data. In this setting, random effect specifications are typically based on a Gaussian Markov random field; however, in the presence of outliers, or discontinuities, models based on non-Gaussian random effects may be more appropriate. We develop a modeling formulation for generalizing the Gaussian CAR model to the non-Gaussian case, allowing for asymmetric marginal distributions having flexible tail behavior through the parametric skew-t distribution. The skew-t formulation, which can be derived as a parametric scale mixture, is then generalized to a semiparametric model based on Dirichelet process scale mixing. The methodology is illustrated in an analysis of health system utilization, mapping rates of revascularization for cardiac patients in Quebec, Canada.
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