JSM 2011 Online Program

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Abstract Details

Activity Number: 529
Type: Contributed
Date/Time: Wednesday, August 3, 2011 : 10:30 AM to 12:20 PM
Sponsor: Social Statistics Section
Abstract - #301466
Title: Meta-Analysis of Multivariate Outcomes: A Monte Carlo Comparison of Alternative Strategies
Author(s): Corina M. Owens*+ and Jeffrey Kromrey and Julie Gloudemans
Companies: University of South Florida and University of South Florida and University of South Florida
Address: 4202 E. Fowler Avenue, Tampa, FL, 33620-7750, United States
Keywords: meta-analysis ; multivariate ; random effects ; multilevel models
Abstract:

Models for meta-analysis are based on the assumption that effect sizes are independent of each other. However, multiple outcomes and treatments from the same study make the tenability of this assumption doubtful. Several meta-analytic methods have been proposed to handle dependent effect sizes: a multivariate multi-level approach (Kalaian & Raudenbush, 1996); Hedges, Tipton, and Johnson's (2010) robust variance estimation strategy; and Gleser and Olkin's (2009) stochastically dependent effect size approach. This research used Monte Carlo methods to compare these approaches to a traditional univariate random effects approach (Hedges & Olkin, 1989). Factors investigated included (a) number of studies included in the meta-analysis, (b) population mean effect sizes, (c) covariance between the effect sizes, (d) within study sample size, and (e) population effect size variance. Accuracy and pr


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