In the food industry, sensory analysis can be useful to direct marketing decisions concerning
not only products, for example product positioning with respect to competitors, but also …

This chapter is devoted to a new class of statistical models, called CUB models, introduced
for the purpose of interpreting and fitting ordinal responses. After a brief discussion of …

Abstract Using data from Italy (1994–2018), we investigate gender differences in consumers'
inflation perceptions over time. We introduce a dynamic model in order to detect the …

In this paper we present two statistical approaches for discussing and modelling job
satisfaction based on data collected in the S urvey on H ousehold I ncome and W ealth …

Ordinal measurements as ratings, preference and evaluation data are very common in
applied disciplines, and their analysis requires a proper modelling approach for …

In several applied disciplines, as Economics, Marketing, Business, Sociology, Psychology,
Political science, Environmental research and Medicine, it is common to collect data in the …

In CUB models the uncertainty of choice is explicitly modelled as a Combination of discrete
Uniform and shifted Binomial random variables. The basic concept to model the response as …

Literature on the models for ordinal variables grew very fast in the last decades and several
proposals have been advanced when ordered data are expression of ratings, preferences …

We introduce cube models with covariates, a class of discrete mixture distributions able to
take uncertainty and overdispersion of ordinal data into account. The main result of the …

The paper is framed within the literature around Louis' identity for the observed information
matrix in incomplete data problems, with a focus on the implied acceleration of maximum …