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20062025
most citedLatent Markov model for longitudinal binary data: An application to the performance evaluation of nursing homes

64 citations · 77 across the 15 of their papers we have counts for

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Showing 2012Show all

6 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 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…

math.ST2012

Causal inference in paired two-arm experimental studies under non-compliance with application to prognosis of myocardial infarction

F. Bartolucci, A. Farcomeni

Motivated by a study about prompt coronary angiography in myocardial infarction, we propose a method to estimate the causal effect of a treatment in two-arm experimental studies wi…

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…

math.ST2012★ 1 cited

Nested hidden Markov chains for modeling dynamic unobserved heterogeneity in multilevel longitudinal data

F. Bartolucci, M. Lupparelli

In the context of multilevel longitudinal data, where sample units are collected in clusters, an important aspect that should be accounted for is the unobserved heterogeneity betwe…