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metaSEM: an R package for meta-analysis using structural equation modeling.

Mike W-L Cheung1

  • 1Department of Psychology, National University of Singapore Singapore, Singapore.

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Summary
This summary is machine-generated.

The metaSEM package in R enables advanced meta-analyses using structural equation modeling (SEM). It supports univariate, multivariate, and multi-level analyses for robust research synthesis.

Keywords:
Rmeta-analysismeta-analytic structural equation modelingmetaSEMstructural equation modeling

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Area of Science:

  • Statistics
  • Psychometrics
  • Quantitative Psychology

Background:

  • Meta-analysis is crucial for synthesizing research findings.
  • Structural Equation Modeling (SEM) offers advanced statistical modeling capabilities.
  • Integrating meta-analysis with SEM provides a powerful framework for complex data synthesis.

Purpose of the Study:

  • To introduce the metaSEM package in R for advanced meta-analysis.
  • To demonstrate the application of SEM for meta-analytic research.
  • To outline theoretical underpinnings and practical implementation of SEM-based meta-analysis.

Main Methods:

  • Utilizes the OpenMx package within the R statistical platform.
  • Implements univariate, multivariate, and three-level meta-analyses.
  • Applies a two-stage SEM approach for fixed- and random-effects meta-analyses on correlation or covariance matrices.

Main Results:

  • The metaSEM package facilitates sophisticated meta-analytic procedures.
  • Demonstrates the formulation of meta-analyses as SEMs.
  • Provides practical examples for applying SEM-based meta-analysis.

Conclusions:

  • SEM-based meta-analysis offers a flexible and powerful approach to research synthesis.
  • The metaSEM package enhances the capabilities for conducting complex meta-analyses.
  • Further exploration of SEM applications in meta-analysis is warranted.