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

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Summary
This summary is machine-generated.

A new meta-analytic structural equation modeling (MASEM) approach, one-stage MASEM, enhances the explanation of study heterogeneity. This method incorporates moderators without requiring complete primary study data, improving meta-analytic research.

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Area of Science:

  • Psychometrics
  • Quantitative Psychology
  • Statistical Modeling

Background:

  • Meta-analytic structural equation modeling (MASEM) integrates meta-analysis and structural equation modeling.
  • Existing MASEM methods have limitations in explaining study-level heterogeneity.
  • MASEM allows evaluation of theoretical models and accounts for sampling covariance.

Purpose of the Study:

  • Introduce a novel one-stage MASEM method to better explain study-level heterogeneity.
  • Enable the incorporation of continuous or categorical moderators into MASEM.
  • Develop a flexible MASEM approach that does not require complete primary study data.

Main Methods:

  • Propose the one-stage MASEM technique.
  • Model structural equation model parameters (e.g., path coefficients, factor loadings) using moderator variables.
  • Illustrate the method with real data sets and evaluate performance via simulation.

Main Results:

  • The one-stage MASEM method effectively explains study-level heterogeneity.
  • The approach accommodates moderator variables in the meta-analytic structural equation model.
  • User-friendly R-functions and syntax are provided for practical application.

Conclusions:

  • One-stage MASEM offers an advancement for meta-analytic research, particularly in handling heterogeneity.
  • The method provides a robust framework for integrating moderators into complex meta-analytic models.
  • Future research directions are outlined for further development and application of MASEM.