The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Online Program Home
Abstract Details
Activity Number:
|
448
|
Type:
|
Topic Contributed
|
Date/Time:
|
Wednesday, August 1, 2012 : 8:30 AM to 10:20 AM
|
Sponsor:
|
Section on Statistics in Epidemiology
|
Abstract - #304474 |
Title:
|
Bayesian Lasso Regression for Zero-Inflated Spatial Data
|
Author(s):
|
Rajib Paul*+ and Magdalena Niewiadomska-Bugaj and Amy B. Curtis and Catherine L. Kothari
|
Companies:
|
Western Michigan University and Western Michigan University and Western Michigan University and Western Michigan University
|
Address:
|
1903 W Michigan Ave-5508 Everett Tower, Kalamazoo, MI, 49008, United States
|
Keywords:
|
conditional autoregressive model ;
diabetes rate ;
logistic regression ;
Poisson Distribution
|
Abstract:
|
In regression analysis for zero inflated data, two quantities are modeled in terms of linear functions of covariates - the probability of observing zeros, which is usually modeled through logistic regression and the nonzero mean function. We consider multivariable spatially correlated response variables, where the spatial dependence is modeled through multivariate conditional autoregressive (MCAR) models. Bayesian LASSO receives a great deal of importance for its ability in variable selection. We develop lasso-type priors for regression coefficients, which enables us to identify important covariates in a pool. We apply our approach to Michigan health policy data on diabetes rates and all our inferences are based on a Markov Chain Monte Carlo algorithm.
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2012 program
|
2012 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.