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Educational and Psychological Measurement, Vol. 67, No. 5, 765-783 (2007)
DOI: 10.1177/0013164407301532

How to Meta-Analyze Coefficient-of-Stability Estimates

Some Recommendations Based on Monte Carlo Studies

Corinne Mason

University of South Florida

Reynald Allam

Morton Plant Hospital Hyperbaric Center

Michael T. Brannick

University of South Florida, mbrannic{at}luna.cas.usf.edu

Reliability generalization studies have provided estimates of the mean reliability coefficients and examined factors that explain the variability in the reliability estimates across studies for many different tests and measures. Different authors have used different data analyses to do such meta-analyses, and little research has addressed whether some methods are more accurate than others. Three methods of meta-analysis for reliability data were compared using Monte Carlo techniques. The meta-analytic methods were those described by Hedges and Vevea, Hunter and Schmidt, and Vacha-Haase. The results suggested that a combination of methods worked best and that Hunter and Schmidt's method should be used to estimate the mean and random-effect variance component, but weighted regression should be used to model continuous moderators.

Key Words: reliability generalization • meta-analysis • Monte Carlo


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