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TECHNIQUE FOR MINIMIZING THE INSTRUMENTAL FACTOR.

R B Mefferd

    Multivariate Behavioral Research
    |January 16, 2016
    PubMed
    Summary

    This study introduces a direct factor score method for comparing data from multiple sources, effectively minimizing instrumental factors. This new technique proved superior, yielding clearer and more numerous factors than the hypothesis matrix method.

    Area of Science:

    • Psychometrics
    • Quantitative Psychology
    • Behavioral Science

    Background:

    • Comparing data from different measurement tools (media) can be challenging due to instrumental factors.
    • Existing methods like the hypothesis matrix technique may not fully resolve these instrumental factor issues.
    • Orthogonal factor scores offer a potential solution for more accurate cross-media comparisons.

    Purpose of the Study:

    • To introduce and evaluate a novel technique using orthogonal factor scores for comparing item-scores across different measurement media.
    • To minimize the impact of instrumental factors in multi-source data analysis.
    • To compare the effectiveness of the direct factor score method against the hypothesis matrix technique.

    Main Methods:

    • The study describes a technique employing orthogonal factor scores to analyze item-scores from multiple media.

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  • A comparative analysis was conducted using data from a behavior rating scale and a structured psychiatric interview scale.
  • The direct factor score method was directly contrasted with the hypothesis matrix technique.
  • Main Results:

    • The direct factor score method demonstrated greater effectiveness compared to the hypothesis matrix technique.
    • This method resulted in larger factor loadings, indicating stronger relationships between variables and factors.
    • Consequently, the direct factor score method facilitated the extraction of a greater number of distinct and well-defined factors.

    Conclusions:

    • The direct factor score method is a more effective approach for comparing item-scores across different measurement media.
    • Its ability to yield larger loadings leads to the identification of more numerous and clearly delineated factors.
    • This technique offers an improved solution for addressing the instrumental factor problem in psychometric research.