JSM 2012 Home

JSM 2012 Online Program

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: 302
Type: Contributed
Date/Time: Tuesday, July 31, 2012 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Statistical Science
Abstract - #306467
Title: Bayesian Adaptive Calibration and Variable Selection in Linear Models with Mismeasured Covariates
Author(s): Hongmei Zhang*+ and Xianzheng Huang and Jianjun Gan and Wilfried Karmaus and Tara Sabo-Attwood
Companies: University of South Carolina and University of South Carolina and GlaxoSmithKline and University of South Carolina and University of Florida
Address: 317B, Health Sci. Bldg., Columbia, SC, 29208, United States
Keywords: g-prior ; Measurement Error ; Prediction Loss ; Pseudo Variables ; Tuning Parameter
Abstract:

We propose a Bayesian variable selection method built upon an extended Zellner's $g$-prior in linear measurement error models. Pseudo variables are introduced into the model to facilitate choosing a tuning parameter that indirectly controls the selection of variables. Simulation results indicate that models selected using the proposed method are generally more favorable with smaller prediction losses than the models selected using classical Zellner's $g$-priors. The proposed method is further demonstrated using two data sets: gene expression data from a lung disease study and food frequency questionnaire data from a nurse study.


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.