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Discrimination Measures Using Contingency Tables.

J E Everett

    Multivariate Behavioral Research
    |January 14, 2016
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    Summary
    This summary is machine-generated.

    Measuring organizational discrimination, such as race or sex discrimination, requires robust methods. This study proposes a loglinear modelling approach using contingency tables to establish reliable measures of direct and total discrimination.

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    Area of Science:

    • Organizational behavior
    • Statistical modeling
    • Sociology

    Background:

    • Discrimination based on race or sex in organizations is a significant issue.
    • Existing linear models for measuring discrimination have limitations in validity.
    • There is a need for reliable measures to compare discrimination across organizations and over time.

    Purpose of the Study:

    • To propose and validate a new statistical method for measuring discrimination.
    • To distinguish between direct and total discrimination using loglinear models.
    • To provide a statistically testable measure for organizational discrimination.

    Main Methods:

    • Utilized a contingency table approach with categorical variables (rank, sex, qualifications).
    • Employed loglinear modelling of odds ratios across ranks to derive maximum likelihood measures.
    • Compared the proposed measure with existing methods like Mantel-Haenszel and collapsed subtable measures.

    Main Results:

    • Developed a maximum likelihood measure capable of distinguishing direct and total discrimination.
    • Demonstrated that the proposed discrimination measure follows a chi-square distribution, allowing for significance testing.
    • The method was successfully applied to assess sex discrimination in an Australian university's staff ranks.

    Conclusions:

    • The proposed loglinear modelling approach offers a valid and statistically sound method for measuring organizational discrimination.
    • This method can be applied to various subgroups and employment contexts for comparative analysis.
    • The findings enhance the potential for sensible discussion and policy development regarding workplace discrimination.