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

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.