A class of Item Response Theory (IRT) models for binary and ordinal polytomous items is illustrated and an R package for dealing with these models, named MultiLCIRT, is described. The models at issue extend traditional IRT models allowing for multidimensionality and discreteness of latent...

Given a random sample of observations, mixtures of normal densities are often used to estimate the unknown continuous distribution from which the data come. The use of this semi-parametric framework is proposed for testing symmetry about an unknown value. More precisely, it is shown how the null...

type="main" xml:id="rssc12030-abs-0001" <title type="main">Summary</title> <p>Motivated by an application to a longitudinal data set coming from the Health and Retirement Study about self-reported health status, we propose a model for longitudinal data which is based on a latent process to account for the unobserved...</p>

We prove a theorem concerning the parameters of the cub  mixture distribution when this random variable is applied for modelling rank data by assuming that the cub  distribution is true for each marginal random variable originated by ordering m objects.

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 market segmentation, customer relationship management, advertising strategies and price policies. In this paper...

In this paper, we propose preliminary estimators for the parameters of a mixture distribution introduced for the analysis of ordinal data where the mixture components are given by a Combination of a discrete Uniform and a shifted Binomial distribution (<Emphasis Type="SmallCaps">cub model). After reviewing some...</emphasis>

The paper proposes a latent class version of Combination of Uniform and (shifted) Binomial random variables ( <Emphasis FontCategory="NonProportional">CUB ) models for ordinal data to account for unobserved heterogeneity. The extension, called  <Emphasis FontCategory="NonProportional">LC-CUB , is useful when the heterogeneity is originated by clusters of respondents not...</emphasis></emphasis>