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Checking the inventory: Illustrating different methods for individual participant data meta-analytic structural

Lennert J Groot1, Kees-Jan Kan1, Suzanne Jak1

  • 1University of Amsterdam, Amsterdam, The Netherlands.

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This study compares structural equation modeling (SEM) methods using raw data for meta-analysis. Results show differences in parameter estimates and standard errors across techniques, highlighting the need for further research on individual participant data meta-analysis.

Keywords:
IPDmeta‐analysismeta‐analytic structural equation modelingraw data synthesisstructural equation modeling

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Area of Science:

  • Psychological Methods
  • Statistical Modeling
  • Meta-Analysis

Background:

  • Researchers often have access to raw data for meta-analyses.
  • Structural Equation Modeling (SEM) is a powerful tool for analyzing complex relationships.

Purpose of the Study:

  • To identify, illustrate, and compare SEM analysis options when raw data are available.
  • To discuss differences in procedures, capabilities, and outcomes of various SEM techniques.

Main Methods:

  • Directly analyzing raw data using multilevel and multigroup SEM.
  • Using summary statistics with correlation-based meta-analytical SEM (MASEM).
  • Fitting a path model based on the theory of planned behavior to multiple datasets using open-source software.

Main Results:

  • Differences observed in parameter estimates and standard errors across methods.
  • Variations in handling missing data, including study-level moderators, and conceptualizing heterogeneity.
  • Direct data analysis and summary statistic-based approaches yield distinct outcomes.

Conclusions:

  • Applied researchers need clear guidelines for conducting individual participant data MASEM.
  • Further research is essential to establish best practices for meta-analytical SEM with raw data.