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Random-effects models for meta-analytic structural equation modeling: review, issues, and illustrations.

Mike W-L Cheung1, Shu Fai Cheung2

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Summary
This summary is machine-generated.

This study explores random-effects models in meta-analytic structural equation modeling (MASEM), comparing correlation-based and parameter-based approaches. It provides guidelines for selecting the appropriate model for synthesizing research findings.

Keywords:
R statistical platformmeta-analysismeta-analytic structural equation modelrandom-effects modelstructural equation model

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Area of Science:

  • Psychometrics
  • Statistical Modeling
  • Quantitative Psychology

Background:

  • Meta-analytic structural equation modeling (MASEM) integrates meta-analysis and structural equation modeling.
  • MASEM synthesizes correlation or covariance matrices to fit structural equation models.
  • While fixed-effects models are common, random-effects models in MASEM are less explored.

Purpose of the Study:

  • To address issues concerning random-effects models within MASEM.
  • To compare two distinct random-effects models: correlation-based MASEM and parameter-based MASEM.
  • To delineate the strengths and limitations of each model and offer practical selection guidelines.

Main Methods:

  • Comparative analysis of correlation-based and parameter-based random-effects MASEM.
  • Illustration through two distinct empirical examples.
  • Exploration of model similarities, differences, and practical application.

Main Results:

  • Detailed comparison of correlation-based and parameter-based random-effects MASEM.
  • Identification of strengths and limitations for each approach.
  • Provision of practical guidance for researchers on model selection.

Conclusions:

  • Random-effects models in MASEM offer valuable approaches for synthesizing research data.
  • Understanding the nuances between correlation-based and parameter-based MASEM is crucial for appropriate application.
  • Further research is needed to fully elucidate the potential of random-effects models in MASEM.