JSM 2004 - Toronto

Abstract #301639

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Activity Number: 225
Type: Contributed
Date/Time: Tuesday, August 10, 2004 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #301639
Title: A Comparison of Frequentist and Bayesian Spatial Regression Approaches
Author(s): Sanjeev Sridharan*+ and Robert M. Baskin
Companies: Westat and Agency for Healthcare Research and Quality
Address: 1650 Research Blvd., Rockville, MD, 20850,
Keywords: spatial regression ; maximum likelihood ; Mlwin ; WinBugs ; multilevel models ; Gibbs sampling
Abstract:

From 1994 to 2000, both crime rates and unemployment rates declined across most of the United States. The cause of such a decline in crime rates remains unclear to most criminologists. Using spatial panel data models, we attempt to link the trajectories of unemployment rates to crime rates. Annual data from Virginia counties and cities between 1994 to 2000 are used to study this relationship.This paper focuses on a comparison of Frequentist to Bayesian spatial regression models. Specifically, we compare a spatial lagged panel model developed using the following three methods: maximum likelihood techniques developed within a spatial econometric framework; spatial multilevel model using iterative generalized least squares procedures in Mlwin based on empirical Bayes methods; Markov chain Monte Carlo methods using Gibbs sampling based on Bayesian methods using the WinBUGS software. Implications of the results for spatial epidemiology are discussed.

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