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A guide for applying principal-components analysis and confirmatory factor analysis to quantitative

J E Arruda1, M D Weiler, D Valentino

  • 1Department of Psychiatry and Human Behavior, Brown University School of Medicine, Providence, RI, USA. arruda_je@mercer.edu

International Journal of Psychophysiology : Official Journal of the International Organization of Psychophysiology
|August 1, 1996
PubMed
Summary

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Principal-components analysis (PCA) in quantitative electroencephalogram (qEEG) research can yield unstable results due to small sample sizes. This study validates a seven-component qEEG solution using confirmatory factor analysis (CFA), demonstrating its stability and reliability.

Area of Science:

  • Neuroscience
  • Psychometrics
  • Signal Processing

Background:

  • Quantitative electroencephalogram (qEEG) research often employs principal-components analysis (PCA) for dimensionality reduction.
  • Small sample sizes in previous qEEG PCA studies have led to unstable component solutions.
  • Independent validation of qEEG component solutions using confirmatory factor analysis (CFA) is lacking.

Purpose of the Study:

  • To illustrate the application of PCA and CFA to qEEG data.
  • To establish decision rules for applying PCA and CFA in qEEG research.
  • To validate a qEEG component solution using an independent sample.

Main Methods:

  • PCA was performed on qEEG measures from 102 healthy individuals during an auditory continuous performance task.

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  • The resulting component solution was validated using CFA in an independent sample of 106 healthy individuals.
  • Internal consistency and test-retest reliability of the validated component solution were assessed.

    • Main Results:

    • A stable, oblique, seven-component solution for qEEG measures was confirmed via CFA.
    • The seven-component solution demonstrated high internal consistency and test-retest reliability.
    • The findings support the use of qEEG data as a stable and valid neurophysiological measure.

    Conclusions:

    • The validated seven-component qEEG solution offers a reliable method for neurophysiological assessment.
    • These qEEG measures may aid in differentiating between clinical and control populations.
    • The study highlights the importance of rigorous validation methods like CFA in qEEG research.