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This study introduces two frameworks for integrating mediation analysis results. These methods, using multivariate meta-analysis and meta-analytic structural equation modeling, synthesize findings from multiple studies to understand indirect and direct effects.

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Area of Science:

  • Psychology
  • Statistics
  • Social Sciences

Background:

  • Mediation analysis explains mechanisms between variables.
  • Synthesizing findings across studies is crucial for robust conclusions.
  • Meta-analysis is a standard method for aggregating research results.

Purpose of the Study:

  • To present two novel frameworks for integrating studies using mediation analysis.
  • To provide researchers with advanced methods for synthesizing indirect and direct effects.
  • To enhance the reliability and generalizability of mediation findings.

Main Methods:

  • Framework 1: Multivariate meta-analysis of standardized indirect and direct effects.
  • Framework 2: Meta-analytic structural equation modeling on average correlation matrices.
  • Illustration using the R statistical platform on a real dataset.

Main Results:

  • Demonstrated practical application of both meta-analytic frameworks.
  • Showcased the synthesis of mediation models across multiple studies.
  • Provided a reproducible example using real-world data.

Conclusions:

  • The proposed frameworks offer powerful tools for advancing mediation research.
  • These methods facilitate more comprehensive understanding of complex variable relationships.
  • Future research directions for enhancing mediation synthesis are discussed.