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    Area of Science:

    • Psychometrics
    • Factor Analysis
    • Personality Psychology

    Background:

    • Psychometric reliability is crucial for the scientific validity of factor analysis.
    • Generalizability across samples is a key aspect of factor reliability.
    • Existing methods may not adequately ensure the meaningfulness of factor analytic results.

    Purpose of the Study:

    • To propose and empirically demonstrate a method for assessing factor generalizability.
    • To establish the psychometric reliability of factors measuring response styles and personality dimensions.
    • To provide a practical approach for routine incorporation into factor analytic investigations.

    Main Methods:

    • Utilized parallel sets of measures for personality scales across seven factors.
    • Performed separate factor analyses on each set of measures.
    • Computed intercorrelations between independent component scores derived from factor patterns to determine factor reliabilities.

    Main Results:

    • Factor reliabilities ranged from .66 to .86 (p < .0001), indicating significant generalizability.
    • Analysis using random binary data yielded nonsignificant factor reliabilities (ranging from -.12 to +.07).
    • The proposed method successfully distinguished reliable factors from chance findings.

    Conclusions:

    • The demonstrated method provides a reliable assessment of factor generalizability.
    • Routine implementation of this factor reliability test is recommended for factor analytic studies.
    • This approach enhances the scientific meaningfulness and robustness of factor analytic findings, especially with Procrustes-type rotations.