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Abstract Details

Activity Number: 39
Type: Contributed
Date/Time: Sunday, July 29, 2012 : 2:00 PM to 3:50 PM
Sponsor: IMS
Abstract - #305257
Title: A Bayesian Approach for a Spatial Probit Model for Complex Survey Data: An Application with Chilean Crime Survey Data
Author(s): Rolando De La Cruz*+ and Cristian Meza
Companies: Pontificia Universidad Católica de Chile and Universidad de Valparaiso
Address: Marcoleta 434, Santiago, _, 8330073, Chile
Keywords: Probit model ; Random effects ; Spatial correlation ; MCMC methods ; Complex survey data ; Crime

Generalized linear models are popular tools to study normal and non-normal data. They can fit spatial-dependent data and a popular model in this class is the probit-normal model. In this study, we analyze complex survey data when units are sampled with unequal probability. We propose a Bayesian approach to estimate the model parameters in this complex spatial probit model. We illustrate our method with data of 2009 Chilean Crime Victimization Survey Data. Work funded by grant ANILLO ACT87.

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