JSM 2004 - Toronto

Abstract #301757

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Activity Number: 85
Type: Contributed
Date/Time: Monday, August 9, 2004 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics and the Environment
Abstract - #301757
Title: Spatial-temporal Hierarchical Poisson Model to Study Association between Speciated Fine Particles and Human Health Effects from Pollution
Author(s): Hae-Ryoung Song*+ and Montserrat Fuentes
Companies: North Carolina State University and North Carolina State University
Address: Dept. of Statistics, 2501 Founders Dr., Raleigh, NC, 27695-8203,
Keywords: mortality ; generalized Poisson regression model ; Bayesian hierarchical model ; space-time series
Abstract:

Many epidemiologic studies have shown the evidence for statistically significant effects of particular matter (PM) on mortality across many areas of the country. The main objective of our research is to quantify uncertainties about the impacts of fine PM exposure on mortality. We develop a multivariate spatial regression model for better estimation of the mortality effects from fine PM and its components across the coterminous U.S. We consider a flexible Bayesian hierarchical model for a space-time series of (mortality) counts by constructing a likelihood based version of a generalized Poisson regression model. We apply these methods to daily mortality county counts, measurements of total and several components of fine PM from national monitoring networks in the U.S.

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