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    This study introduces a statistical method to analyze individual personality structure into component factors using common responses from a representative subject sample. The approach is further developed to differentiate categories of individuals based on response patterns.

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    Area of Science:

    • Psychometrics
    • Statistical analysis
    • Personality psychology

    Background:

    • Understanding individual personality structure is crucial in psychology.
    • Existing methods may lack detailed statistical breakdown of personality components.

    Purpose of the Study:

    • To present a statistical method for analyzing an individual's personality structure into component factors.
    • To expand this method for differentiating categories of individuals.

    Main Methods:

    • Statistical analysis of individual responses against a representative subject sample.
    • Pattern selection for differentiating between categories of individuals.

    Main Results:

    • Demonstrated a method to statistically decompose personality into component types (factors).
    • Developed a pattern-based approach for individual category differentiation.

    Conclusions:

    • The proposed statistical framework effectively analyzes and differentiates personality structures.
    • This method offers a novel approach to understanding individual and group personality differences.