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Combining Standardized Mean Differences Using the Method of Maximum Likelihood

Published online by Cambridge University Press:  01 January 2025

Ke-Hai Yuan  and
Brad J. Bushman
Ke-Hai Yuan*
Affiliation:
University of Notre Dame
Brad J. Bushman
Affiliation:
Iowa State University
*
Requests for reprints should be sent to Ke-Hai Yuan, Laboratory for Social Research, 919 Flanner Hall, University of Notre Dame IN 46556. E-Mail: kyuan@nd.edu
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Abstract

A maximum likelihood procedure for combining standardized mean differences based on a noncentratt-distribution is proposed. With a proper data augmentation technique, an EM-algorithm is developed. Information and likelihood ratio statistics are discussed in detail for reliable inference. Simulation results favor the proposed procedure over both the existing normal theory maximum likelihood procedure and the commonly used generalized least squares procedure.

Keywords

noncentral t-distributiondata augmentationEM-algorithmobserved informationMonte-Carlometa-analysiseffect sizemaximum likelihoodweighted least squares

Information

Type
Articles
Information
Psychometrika , Volume 67 , Issue 4 , December 2002 , pp. 589 - 607
Copyright
Copyright © 2002 The Psychometric Society

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