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Correlation-Based Meta-Analytic Structural Equation Modeling: Effects of Parameter Covariance on Point and Interval Estimates
Shu Fai Cheung1; Rong Wei Sun11; Darius K.-S. Chan2
2018-05-08
Source PublicationOrganizational Research Methods
ISSN10944281
Pages1-25
Abstract

More and more researchers use meta-analysis to conduct multivariate analysis to summarize previous findings. In the correlation-based meta-analytic structural equation modeling (cMASEM), the average sample correlation matrix is used to estimate the average population model. Using a simple mediation model, we illustrated that random effects covariation in population parameters can theoretically bias the path coefficient estimates and lead to nonnormal random effects distribution of the correlations. We developed an R function for researchers to examine by simulation the impact of random effects in other models. We then reanalyzed two real data sets and conducted a simulation study to examine the magnitude of the impact on realistic situations. Simulation results suggest parameter bias is typically negligible (less than .02), parameter bias and root mean square error do not differ across methods, 95% confident intervals are sometimes more accurate for the two-stage structural equation modeling approach with a diagonal random effects model, and power is sometimes higher for the traditional Viswesvaran-Ones approach. Given the increasing popularity of cMASEM in organizational research, these simulation results form the basis for us to make several recommendations on its application.

KeywordMeta-analysis Structural Equation Modeling Meta-analytic Structural Equation Modeling
DOI10.1177/1094428118770736
Language英语
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Document TypeJournal article
CollectionDEPARTMENT OF PSYCHOLOGY
Corresponding AuthorShu Fai Cheung
Affiliation1.University of Macau, Macao SAR, China
2.The Chinese University of Hong Kong, Sha Tin, Hong Kong
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Shu Fai Cheung,Rong Wei Sun1,Darius K.-S. Chan. Correlation-Based Meta-Analytic Structural Equation Modeling: Effects of Parameter Covariance on Point and Interval Estimates[J]. Organizational Research Methods,2018:1-25.
APA Shu Fai Cheung,Rong Wei Sun1,&Darius K.-S. Chan.(2018).Correlation-Based Meta-Analytic Structural Equation Modeling: Effects of Parameter Covariance on Point and Interval Estimates.Organizational Research Methods,1-25.
MLA Shu Fai Cheung,et al."Correlation-Based Meta-Analytic Structural Equation Modeling: Effects of Parameter Covariance on Point and Interval Estimates".Organizational Research Methods (2018):1-25.
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