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Discussion of ‘The class of CUB models: statistical foundations, inferential issues and empirical evidence’ by Domenico Piccolo and Rosaria Simone

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  • Leonardo Grilli

    (University of Florence)

  • Carla Rampichini

    (University of Florence)

Abstract

In this note we briefly discuss the structure of CUB models and their interpretation. Furthermore, we elaborate some issues related to the comparison of CUB models with mainstream approaches, focusing on generalized linear models for univariate ordinal responses and classical latent variable models for multivariate ordinal responses.

Suggested Citation

  • Leonardo Grilli & Carla Rampichini, 2019. "Discussion of ‘The class of CUB models: statistical foundations, inferential issues and empirical evidence’ by Domenico Piccolo and Rosaria Simone," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 459-463, September.
    • Handle: RePEc:spr:stmapp:v:28:y:2019:i:3:d:10.1007_s10260-019-00466-w
    DOI: 10.1007/s10260-019-00466-w
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    References listed on IDEAS

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    1. Geoff Masters, 1982. "A rasch model for partial credit scoring," Psychometrika, Springer;The Psychometric Society, vol. 47(2), pages 149-174, June.
    2. Domenico Piccolo & Rosaria Simone, 2019. "The class of cub models: statistical foundations, inferential issues and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 389-435, September.
    3. R. Darrell Bock, 1972. "Estimating item parameters and latent ability when responses are scored in two or more nominal categories," Psychometrika, Springer;The Psychometric Society, vol. 37(1), pages 29-51, March.
    4. Manisera, Marica & Zuccolotto, Paola, 2014. "Modeling rating data with Nonlinear CUB models," Computational Statistics & Data Analysis, Elsevier, vol. 78(C), pages 100-118.
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