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Meta-Analysing the Factor Structure and Reliability of Measurement Instruments: An R-Based Tutorial.

Maximiliano Escaffi-Schwarz1, René Gempp1, Julien P Irmer2

  • 1Facultad de Administración y Economía, Universidad Diego Portales, Santiago, Chile.

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Summary
This summary is machine-generated.

This study introduces meta-analytical methods to evaluate scale measurement quality, focusing on factor structure and reliability. These tools enhance research replicability and comparability in psychology.

Keywords:
Reliability Generalizationfactor analysismeta‐SEMmeta‐analysisquantitative tutorial

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Area of Science:

  • Psychological Measurement
  • Quantitative Psychology
  • Psychometrics

Background:

  • Meta-analyses commonly focus on effect sizes, often neglecting the crucial measurement quality of underlying scales.
  • Poor measurement quality can compromise statistical inferences in studies utilizing multi-item scales.

Purpose of the Study:

  • To introduce and illustrate meta-analytical techniques for assessing scale measurement quality, specifically factor structure and reliability.
  • To provide R scripts for implementing these methods, aiding psychological researchers.

Main Methods:

  • Utilized 12 samples of the Dirty Dozen questionnaire for dark triad personality assessment.
  • Demonstrated two methods for meta-analytically assessing scale factor structure based on available data.
  • Illustrated the Reliability Generalization method for meta-analytically assessing scale reliability.

Main Results:

  • Provided R scripts for assessing scale factor structure and reliability through meta-analysis.
  • Discussed the strengths and limitations of the presented methods.
  • Offered guidance for researchers on implementing and interpreting these measurement quality assessment techniques.

Conclusions:

  • Equipping researchers with tools to investigate scale measurement quality enhances research replicability, generalizability, and comparability.
  • Meta-analytical assessment of measurement quality is vital for robust psychological research.