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Meta-analytic structural equation modeling with moderating effects on SEM parameters.

Bibliographic Data

ID23355754
AuthorsSuzanne Jak (0000-0002-2223-5594, National University of Singapore), Mike W-L Cheung (0000-0003-0113-0758, National University of Singapore)
Year2020
Volume25
Issue4
Pages430-455
Publication date2020-08-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenuePsychological Methods (JOURNAL)
Journal identifiersISSN: 1082-989X • E-ISSN: 1939-1463
PublisherAmerican Psychological Association (APA) (PUBLISHER)
DOI10.1037/met0000245
PMID31670537
OpenAlexW2947143056
LanguageEN
Citations received65
References cited39

Meta-analytic structural equation modeling (MASEM) is an increasingly popular meta-analytic technique that combines the strengths of meta-analysis and structural equation modeling. MASEM facilitates the evaluation of complete theoretical models (e.g., path models or factor analytic models), accounts for sampling covariance between effect sizes, and provides measures of overall fit of the hypothesized model on meta-analytic data. We propose a novel MASEM method, one-stage MASEM, which is better suitable to explain study-level heterogeneity than existing methods. One-stage MASEM allows researchers to incorporate continuous or categorical moderators into the MASEM, in which any parameter in the structural equation model (e.g., path coefficients and factor loadings) can be modeled by the moderator variable, while the method does not require complete data for the primary studies included in the meta-analysis. We illustrate the new method on two real data sets, evaluate its empirical performance via a computer simulation study, and provide user-friendly R-functions and annotated syntax to assist researchers in applying one-stage MASEM. We close the article by presenting several future research directions. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Categorical variable · Covariance · Data mining · Econometrics · Latent variable · Machine learning · Moderation · Path (computing) · Path analysis (statistics) · Statistics · Structural equation modeling · Artificial Intelligence · Computer Science · Diverse Approaches in Healthcare and Education Studies · Mathematics · Meta-analysis and systematic reviews · Psychometric Methodologies and Testing

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Unique citing works65
Citations per year10,83
Citation span2020 - 2026 (7)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 60

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