Assessing similarity of rating distributions by Kullback-Leibler divergence

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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. © Springer-Verlag Berlin Heidelberg 2011.

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APA

Corduas, M. (2011). Assessing similarity of rating distributions by Kullback-Leibler divergence. In Studies in Classification, Data Analysis, and Knowledge Organization (pp. 221–228). Kluwer Academic Publishers. https://doi.org/10.1007/978-3-642-13312-1_22

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