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Factoring handedness data: II. Geschwind's multidimensional hypothesis

H B Messinger, M I Messinger

    Cortex; a Journal Devoted to the Study of the Nervous System and Behavior
    |June 1, 1996
    PubMed
    Summary
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    This study addresses issues with factor analysis of handedness data, finding that even after normalization, handedness is not unidimensional. Seven factors were identified, supporting previous assertions.

    Area of Science:

    • Psychology
    • Neuroscience
    • Human Behavior

    Background:

    • Factor analysis of handedness data has faced challenges due to data bimodality.
    • Previous attempts to normalize handedness item distributions were insufficient.

    Purpose of the Study:

    • To address the validity concerns raised regarding factor analyses of handedness data.
    • To investigate the dimensionality of handedness by applying optimal data transformations.

    Main Methods:

    • A new survey utilized Oldfield's questionnaire format with 55 handedness items.
    • Optimal data transformations were selected based on D'Agostino's K2 statistic to normalize item distributions.
    • Factor analysis was performed using maximum likelihood and principal components extraction, followed by varimax rotation.

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    Main Results:

    • Out of 55 items, 38 showed unimodal distributions and 11 were marginally bimodal.
    • Optimal transformations normalized all but two handedness item distributions.
    • Seven factors were consistently derived across different extraction methods and rotation, demonstrating high congruence.

    Conclusions:

    • Handedness data normalization is crucial for valid factor analysis.
    • The findings support Geschwind's assertion that handedness is not a unidimensional trait.
    • Factor analysis reveals a multi-faceted nature of handedness.