JSM 2011 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.

Abstract Details

Activity Number: 512
Type: Contributed
Date/Time: Wednesday, August 3, 2011 : 10:30 AM to 12:20 PM
Sponsor: Business and Economic Statistics Section
Abstract - #302649
Title: Posterior Predictive Distributions In Meta-Analysis: An Updated Hunter-Schmidt Analysis Using Bayesian Hierarchical Models
Author(s): David G. Whiting*+ and Michael D. Ulrich
Companies: Brigham Young University and The RBL Group
Address: 223C TMCB, Provo, UT, 84602,
Keywords: posterior predictive distributions ; meta-analysis ; correlations

The traditional Hunter-Schmidt approach to meta-analysis includes fixed effect, random effect, and empirical Bayesian models for combining correlations from multiple studies. When modeling correlations, each of these approaches takes into account corrections for reliability. However, they do not fully account for the uncertainty introduced by estimating the reliability coefficients themselves. We propose a Bayesian hierarchical model for correlation meta-analysis which fully accounts for these sources of model variability. We demonstrate how the posterior predictive distributions of the study correlations yields more information for drawing overall conclusions. We examine a highly-cited meta-analysis from the organizational behavior literature, showing how its conclusions would have been different had reliability uncertainty been accounted for.

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 2011 program

2011 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.