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Mokken Scale Analysis for Dichotomous Items Using Marginal Models.

L Andries van der Ark1, Marcel A Croon, Klaas Sijtsma

  • 1Department of Methodology and Statistics, FSW, Tilburg University, P.O. Box 90153, 5000 LE Tilburg, The Netherlands.

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Summary
This summary is machine-generated.

This study introduces marginal modeling for Mokken scale analysis, enabling hypothesis testing for scalability coefficients. This new framework allows for robust assessment of scale properties and item comparisons.

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Area of Science:

  • Psychometrics
  • Statistical Modeling

Background:

  • Scalability coefficients are crucial in Mokken scale analysis for evaluating measurement instruments.
  • Existing methods for hypothesis testing of these coefficients are underdeveloped.

Purpose of the Study:

  • To introduce marginal modeling as a novel framework for Mokken scale analysis.
  • To develop methods for deriving standard errors and testing hypotheses related to scalability coefficients.

Main Methods:

  • Utilized marginal modeling to derive standard errors for scalability coefficients.
  • Applied the framework to test hypotheses regarding Mokken's scale criteria and coefficient equality.

Main Results:

  • Demonstrated the utility of marginal modeling through several examples.
  • Showcased the ability to test scale satisfaction, item coefficient equality, and cross-group coefficient equality.

Conclusions:

  • Marginal modeling provides a robust framework for hypothesis testing in Mokken scale analysis.
  • This approach enhances the statistical rigor for evaluating measurement scales and comparing items/groups.