Applying meta-analysis to structural equation modeling.
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.
Statistics, Northwestern University, 2040 N. Sheridan Road, Evanston, IL, 60610, USA.
Larry V
LV
Hedges
D000465:Algorithms; D006801:Humans; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D015999:Multivariate Analysis; D013223:Statistics as Topic
Structural equation models; factor analysis; meta-analysis; random effects