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20112021
most citedMixture latent autoregressive models for longitudinal data

2 citations · 4 across the 12 of their papers we have counts for

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Showing 2012Show all

7 papers · 1 filter

stat.AP2012

Joint Assessment of the Differential Item Functioning and Latent Trait Dimensionality of Students' National Tests

Michela Gnaldi, Francesco Bartolucci, Silvia Bacci

Within the educational context, students' assessment tests are routinely validated through Item Response Theory (IRT) models which assume unidimensionality and absence of Different…

stat.ME2012

A causal analysis of mother's education on birth inequalities

Silvia Bacci, Francesco Bartolucci, Luca Pieroni

We propose a causal analysis of the mother's educational level on the health status of the newborn, in terms of gestational weeks and weight. The analysis is based on a finite mixt…

stat.ME2012

A comparison of some criteria for states selection in the latent Markov model for longitudinal data

Silvia Bacci, Silvia Pandolfi, Fulvia Pennoni

We compare different selection criteria to choose the number of latent states of a multivariate latent Markov model for longitudinal data. This model is based on an underlying Mark…

stat.ME2012

A multidimensional latent class Rasch model for the assessment of the Health-related Quality of Life

Silvia Bacci, Francesco Bartolucci

The work describes a multidimensional latent class Rasch model and its application to data about the measurement of some aspects of Health-related Quality of Life and Anxiety and D…

stat.AP2012★ 2 cited

MultiLCIRT: An R package for multidimensional latent class item response models

Francesco Bartolucci, Silvia Bacci, Michela Gnaldi

We illustrate a class of Item Response Theory (IRT) models for binary and ordinal polythomous items and we describe an R package for dealing with these models, which is named Multi…

stat.ME2012

Mixtures of equispaced normal distributions and their use for testing symmetry in univariate data

Silvia Bacci, Francesco Bartolucci

Given a random sample of observations, mixtures of normal densities are often used to estimate the unknown continuous distribution from which the data come. Here we propose the use…