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Utilizing primary study quality in meta-analyses in psychology: A step-by-step tutorial.

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This tutorial guides researchers on incorporating primary study quality (PSQ) into psychological meta-analyses. It offers methods for representing PSQ and testing its impact on findings, enhancing analytical rigor.

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Area of Science:

  • Psychology
  • Research Methodology

Background:

  • Evaluating primary study quality (PSQ) is crucial for psychological meta-analyses to minimize bias and ensure valid inferences.
  • Current guidance on representing and incorporating PSQ is limited, with common methods like sum scores lacking measurement model support.

Purpose of the Study:

  • To provide a tutorial for researchers on representing and incorporating PSQ in meta-analyses.
  • To address the lack of guidance and measurement model backing for common PSQ procedures.

Main Methods:

  • Describing, reviewing, and illustrating approaches to represent PSQ using single or multiple indicators or aggregated scores.
  • Examining the moderator effects of PSQ and testing the sensitivity of moderator effects to PSQ.
  • Providing a step-by-step tutorial with analytic code.

Main Results:

  • The tutorial illustrates various methods for representing PSQ and analyzing its impact.
  • It encourages a measurement perspective when aggregating PSQ indicators.
  • Moderator sensitivity analyses are recommended to assess PSQ's influence.

Conclusions:

  • The study offers practical guidance and tools for researchers to improve the handling of PSQ in meta-analyses.
  • Adopting a measurement perspective and conducting sensitivity analyses can enhance the validity of meta-analytic findings.