Abstract
A mixture model for ordinal data modelling (denoted CUB) has been recently proposed in literature. Specifically, ordinal data are represented by means of a discrete random variable which is a mixture of a Uniform and shifted Binomial random variables. This article proposes a testing procedure based on the Kullback-Leibler divergence in order to compare CUB models and detect similarities in the structure of judgements that raters express on set of items.
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Acknowledgments
This research was partly funded by the MIUR-PRIN 2006 grant (Project on: “Stima e verifica di modelli statistici per l’analisi della soddisfazione degli studenti universitari”) and CFEPSR (Portici, NA).
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Corduas, M. (2011). Assessing Similarity of Rating Distributions by Kullback-Leibler Divergence. In: Fichet, B., Piccolo, D., Verde, R., Vichi, M. (eds) Classification and Multivariate Analysis for Complex Data Structures. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13312-1_22
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DOI: https://doi.org/10.1007/978-3-642-13312-1_22
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