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Applying meta‐analysis to structural equation modeling
Author(s) -
Hedges Larry V.
Publication year - 2016
Publication title -
research synthesis methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.376
H-Index - 35
eISSN - 1759-2887
pISSN - 1759-2879
DOI - 10.1002/jrsm.1214
Subject(s) - structural equation modeling , context (archaeology) , econometrics , computer science , correlation , matrix (chemical analysis) , mathematics , machine learning , paleontology , materials science , geometry , composite material , biology
Structural equation models play an important role in the social sciences. Consequently, there is an increasing use of meta‐analytic methods to combine evidence from studies that estimate the parameters of structural equation models. Two approaches are used to combine evidence from structural equation models: A direct approach that combines structural coefficients and an indirect approach that first combines correlation matrices and estimates structural coefficients from the combined correlation matrix. When there is no heterogeneity across studies, direct estimates of structural coefficients from several studies is an appealing approach. Heterogeneity of correlation matrices across studies presents both practical and conceptual problems. An alternative approach to heterogeneity is suggested as an example of how to better handle heterogeneity in this context. Copyright © 2016 John Wiley & Sons, Ltd.