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Meta-analysis using linear mixed models.

C F Sheu1, S Suzuki

  • 1DePaul University, Chicago, Illinois, USA.

Behavior Research Methods, Instruments, & Computers : a Journal of the Psychonomic Society, Inc
|July 13, 2001
PubMed
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This study introduces linear mixed models for psychological meta-analysis, offering a new framework within the SAS statistical package. This approach simplifies complex data analysis for researchers, enhancing the meta-analysis process.

Area of Science:

  • Psychology
  • Statistics
  • Data Analysis

Background:

  • Meta-analysis is crucial in psychological research for synthesizing study findings.
  • Traditional meta-analysis often requires specialized software.
  • Standard statistical packages historically lacked dedicated meta-analysis procedures.

Purpose of the Study:

  • Introduce linear mixed models as a flexible framework for psychological meta-analysis.
  • Demonstrate the application of these models using a widely-used statistical package.
  • Provide practical examples for researchers to implement the methodology.

Main Methods:

  • Utilized linear mixed models (LMMs) as the core analytical framework.
  • Employed the SAS statistical software package, specifically PROC MIXED.

Related Experiment Videos

  • Illustrated the LMM approach with three distinct meta-analysis examples from psychological research.

    • Main Results:

    • Successfully applied linear mixed models to psychological meta-analysis within SAS.
    • Demonstrated the feasibility and utility of LMMs for synthesizing research findings.
    • Provided practical, reproducible examples of the methodology.

    Conclusions:

    • Linear mixed models offer a robust and accessible framework for meta-analysis in psychology.
    • SAS PROC MIXED can be effectively used for implementing advanced meta-analysis techniques.
    • This approach enhances the capability of psychologists to conduct rigorous meta-analyses.