activity
20092025
most citedAssessment of school performance through a multilevel latent Markov Rasch model

52 citations · 66 across the 6 of their papers we have counts for

collaborators

7 papers

stat.ME2025

Dealing with separation problem in hidden Markov models with covariates based on a penalized maximum likelihood approach

Luca Brusa, Fulvia Pennoni, Francesco Bartolucci +1

A penalized maximum likelihood estimation approach is proposed for discrete-time hidden Markov models where covariates affect the observed responses and serial dependence is consid…

stat.ME2021★ 1 cited

Maximum likelihood estimation of hidden Markov models for continuous longitudinal data with missing responses and dropout

Silvia Pandolfi, Francesco Bartolucci, Fulvia Pennoni

We propose an inferential approach for maximum likelihood estimation of the hidden Markov models for continuous responses. We extend to the case of longitudinal observations the fi…

stat.CO2015★ 11 cited

LMest: an R package for latent Markov models for categorical longitudinal data

Francesco Bartolucci, Alessio Farcomeni, Silvia Pandolfi +1

Latent Markov (LM) models represent an important class of models for the analysis of longitudinal data (Bartolucci et. al., 2013), especially when response variables are categorica…

stat.AP2014

Exploiting TIMSS and PIRLS combined data: multivariate multilevel modelling of student achievement

Leonardo Grilli, Fulvia Pennoni, Carla Rampichini +1

We exploit a multivariate multilevel model for the analysis of the Italian sample of the TIMSS\&PIRLS 2011 Combined International Database on fourth grade students. The multivariat…

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…

math.ST2011★ 2 cited

Mixture latent autoregressive models for longitudinal data

Francesco Bartolucci, Silvia Bacci, Fulvia Pennoni

Many relevant statistical and econometric models for the analysis of longitudinal data include a latent process to account for the unobserved heterogeneity between subjects in a dy…