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Criterion Measures Are Not Always Continuous: Consequential Validity Ratio for Logistic Regression.

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Title: Criterion Measures Are Not Always Continuous: Consequential Validity Ratio for Logistic Regression.
Authors: Dong, Yixiao (AUTHOR), Baral, Kushmakar (AUTHOR), Dumas, Denis (AUTHOR)
Source: Journal of Experimental Education. 2026, Vol. 94 Issue 2, p365-382. 18p.
Subjects: Test validity, Logistic regression analysis, Predictive validity, Evaluation methodology, Simulation methods & models, Test scoring, Psychometrics
Abstract: Neither the theoretical conceptualization of validity, validation methodologies, nor the relative importance of different aspects of validity in measure development, is static over time. With the evolution of social values, validity evidence based on testing consequences has received greater attention in measurement research and practice. However, the methodological basis for generating this type of validity evidence is relatively underdeveloped compared to other psychometric properties (e.g., dimensionality, content validity, and reliability). The Consequential Validity Ratio (CVR) is a recently developed method for quantifying and representing how well test scores avoid the improper influence of participant demographics in the prediction of a validation criterion. The original CVR can only be applied when the criterion measures are continuous; however, binary criteria are also common in scale validation practice. This study theoretically proposes six candidate formulas for the CVR that can be used with binary criteria in a logistic regression framework (i.e., CVRB). A simulation analysis with a two-factor design was conducted to help determine the final formulation of the CVRB. The final formulation is conceptually aligned with the original CVR, straightforward to calculate, intuitive to interpret, and has adequate efficacy in generating evidence for the consequential basis of validity. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Experimental Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Criterion Measures Are Not Always Continuous: Consequential Validity Ratio for Logistic Regression.
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  Data: <searchLink fieldCode="AR" term="%22Dong%2C+Yixiao%22">Dong, Yixiao</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Baral%2C+Kushmakar%22">Baral, Kushmakar</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Dumas%2C+Denis%22">Dumas, Denis</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Experimental+Education%22">Journal of Experimental Education</searchLink>. 2026, Vol. 94 Issue 2, p365-382. 18p.
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  Data: <searchLink fieldCode="DE" term="%22Test+validity%22">Test validity</searchLink><br /><searchLink fieldCode="DE" term="%22Logistic+regression+analysis%22">Logistic regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Predictive+validity%22">Predictive validity</searchLink><br /><searchLink fieldCode="DE" term="%22Evaluation+methodology%22">Evaluation methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+methods+%26+models%22">Simulation methods & models</searchLink><br /><searchLink fieldCode="DE" term="%22Test+scoring%22">Test scoring</searchLink><br /><searchLink fieldCode="DE" term="%22Psychometrics%22">Psychometrics</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Neither the theoretical conceptualization of validity, validation methodologies, nor the relative importance of different aspects of validity in measure development, is static over time. With the evolution of social values, validity evidence based on testing consequences has received greater attention in measurement research and practice. However, the methodological basis for generating this type of validity evidence is relatively underdeveloped compared to other psychometric properties (e.g., dimensionality, content validity, and reliability). The Consequential Validity Ratio (CVR) is a recently developed method for quantifying and representing how well test scores avoid the improper influence of participant demographics in the prediction of a validation criterion. The original CVR can only be applied when the criterion measures are continuous; however, binary criteria are also common in scale validation practice. This study theoretically proposes six candidate formulas for the CVR that can be used with binary criteria in a logistic regression framework (i.e., CVRB). A simulation analysis with a two-factor design was conducted to help determine the final formulation of the CVRB. The final formulation is conceptually aligned with the original CVR, straightforward to calculate, intuitive to interpret, and has adequate efficacy in generating evidence for the consequential basis of validity. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Experimental Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1080/00220973.2024.2369333
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      – Code: eng
        Text: English
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        PageCount: 18
        StartPage: 365
    Subjects:
      – SubjectFull: Test validity
        Type: general
      – SubjectFull: Logistic regression analysis
        Type: general
      – SubjectFull: Predictive validity
        Type: general
      – SubjectFull: Evaluation methodology
        Type: general
      – SubjectFull: Simulation methods & models
        Type: general
      – SubjectFull: Test scoring
        Type: general
      – SubjectFull: Psychometrics
        Type: general
    Titles:
      – TitleFull: Criterion Measures Are Not Always Continuous: Consequential Validity Ratio for Logistic Regression.
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            NameFull: Dong, Yixiao
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            NameFull: Baral, Kushmakar
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            NameFull: Dumas, Denis
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            – D: 01
              M: 04
              Text: 2026
              Type: published
              Y: 2026
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