Varying uncertainty in CUB models

Anna Gottard (), Maria Iannario () and Domenico Piccolo ()
Additional contact information
Anna Gottard: University of Florence
Maria Iannario: University of Naples Federico II
Domenico Piccolo: University of Naples Federico II

Advances in Data Analysis and Classification, 2016, vol. 10, issue 2, No 7, 225-244

Abstract: Abstract This paper presents a generalization of a mixture model used for the analysis of ratings and preferences by introducing a varying uncertainty component. According to the standard mixture model, called CUB model, the response probabilities are defined as a convex combination of shifted Binomial and discrete Uniform random variables. Our proposal introduces uncertainty distributions with different shapes, which could capture response style and indecision of respondents with greater effectiveness. Since we consider several alternative specifications that are nonnested, we suggest the implementation of a Vuong test for choosing among them. In this regard, some simulation experiments and real case studies confirm the usefulness of the approach.

Keywords: Ordinal data; CUB models; Latent classification; Mixture models; 62F99; 62J99 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (12)

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DOI: 10.1007/s11634-016-0235-0

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