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Estimation of Random effect Meta-Analytic Structural Equation Modeling (MASEM) Using Generalized Method of Moments
Rahmawati Erma Standsyah1, Bambang Widjanarko Otok2
1Department of Mathematics, Faculty of Mathematics and Natural Sciences, State University of Surabaya (UNESA), Ketintang, Surabaya, East Java, Surabaya, 60231, Indonesia.
Methodsx
|August 2, 2026
Summary
This study introduces a novel Generalized Method of Moments (GMM) approach for Meta-Analytic Structural Equation Modeling (MASEM) random-effects models. This method effectively addresses data heterogeneity, ensuring unbiased and consistent parameter estimation in correlation-based meta-analyses.
Area of Science:
- Psychometrics
- Statistical Modeling
- Meta-Analysis
Background:
- Meta-Analytic Structural Equation Modeling (MASEM) synthesizes findings from multiple studies using correlation-based effect sizes.
- MASEM models often exhibit significant heterogeneity, necessitating robust estimation methods.
- Existing MASEM estimation often relies on simulation or computational techniques.
Purpose of the Study:
- To introduce a novel Generalized Method of Moments (GMM) approach for estimating parameters in MASEM random-effects models.
- To address the challenge of heterogeneity in MASEM by employing GMM.
- To provide an estimation method with desirable statistical properties like unbiasedness and consistency.
Main Methods:
- The study utilizes a correlation-based effect size derived from ordinary structural equation models.
- The Generalized Method of Moments (GMM) is employed as the primary estimation technique.
- Time series theory's concept of lag is incorporated to manage between-study variance and heterogeneity.
Main Results:
- The GMM estimation method for MASEM random-effects models yields unbiased and consistent parameter estimates.
- This approach offers a new, theoretically grounded method for MASEM parameter estimation.
- The method effectively accounts for heterogeneity by addressing variance between studies.
Conclusions:
- The Generalized Method of Moments (GMM) provides a statistically sound and effective method for estimating parameters in heterogeneous MASEM random-effects models.
- This research offers a significant advancement over traditional simulation-based or computational approaches for MASEM.
- The proposed method enhances the reliability and validity of meta-analytic structural equation modeling.
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