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Nonparametric item response theory using Stata

Author

Listed:
  • Jean-Benoit Hardouin

    (University of Nantes)

  • Angelique Bonnaud-Antignac

    (University of Nantes)

  • Veronique Sebille

    (University of Nantes)

Abstract

Item response theory is a set of models and methods allowing for the analysis of binary or ordinal variables (items) that are influenced by a latent variable or latent trait- that is, a variable that cannot be measured directly. The theory was originally developed in educational assessment but has many other applications in clinical research, ecology, psychiatry, and economics. The Mokken scales have been described by Mokken (1971, A Theory and Procedure of Scale Analysis [De Gruyter]). They are composed of items that satisfy the three fundamental assumptions of item response theory: unidimensionality, monotonicity, and local independence. They can be considered nonparametric models in item response theory. Traces of the items and Loevinger's H coefficients are particularly useful indexes for checking whether a set of items constitutes a Mokken scale. However, these indexes are not available in general statistical packages. We introduce Stata commands to compute them. We also describe the options available and provide examples of output. Copyright 2011 by StataCorp LP.

Suggested Citation

  • Jean-Benoit Hardouin & Angelique Bonnaud-Antignac & Veronique Sebille, 2011. "Nonparametric item response theory using Stata," Stata Journal, StataCorp LP, vol. 11(1), pages 30-51, March.
    • Handle: RePEc:tsj:stataj:v:11:y:2011:i:1:p:30-51
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    References listed on IDEAS

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    1. Xiaohui Zheng & Sophia Rabe-Hesketh, 2007. "Estimating parameters of dichotomous and ordinal item response models with gllamm," Stata Journal, StataCorp LP, vol. 7(3), pages 313-333, September.
    2. Bas Hemker & Klaas Sijtsma & Ivo Molenaar & Brian Junker, 1997. "Stochastic ordering using the latent trait and the sum score in polytomous IRT models," Psychometrika, Springer;The Psychometric Society, vol. 62(3), pages 331-347, September.
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    Cited by:

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    3. Mei Zhang & Xinliang Wang, 2023. "Measurement of Common Prosperity of Chinese Rural Households Using Graded Response Models: Evidence from Zhejiang Province," IJERPH, MDPI, vol. 20(5), pages 1-16, March.
    4. Olivier Beaumais & Mireille Chiroleu-Assouline, 2020. "Informal versus Formal Corporate Social Responsibility: a Tale of Hidden Green Attitude," Working Papers halshs-03073242, HAL.
    5. Monica Szeles & Alessio Fusco, 2013. "Item response theory and the measurement of deprivation: evidence from Luxembourg data," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(3), pages 1545-1560, April.
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    8. Lorenzo Corsini & Irene Martelli, 2020. "Measuring and detecting situations of need and deprivation using Graded Response models," Applied Economics Letters, Taylor & Francis Journals, vol. 27(15), pages 1289-1294, September.
    9. Viktora-Jones, Magdalena & Parente, Ronaldo & Drori, Netanel & Zhao, Yue, 2024. "Firm performance drivers within a dynamic emerging market ecosystem," Journal of International Management, Elsevier, vol. 30(1).
    10. Michael Reichenheim & Wanderson Souza & Evandro Silva Freire Coutinho & Ivan Figueira & Maria Inês Quintana & Marcelo Feijó de Mello & Rodrigo Affonseca Bressan & Jair de Jesus Mari & Sergio Baxter An, 2014. "Structural Validity of the Tonic Immobility Scale in a Population Exposed to Trauma: Evidence from Two Large Brazilian Samples," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-7, April.

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