64 citations · 184 across the 34 of their papers we have counts for
12 papers · 1 filter
Composite likelihood inference in a discrete latent variable model for two-way "clustering-by-segmentation" problems
Francesco Bartolucci, Francesca Chiaromonte, Prabhani Kuruppumullage Don +1
We consider a discrete latent variable model for two-way data arrays, which allows one to simultaneously produce clusters along one of the data dimensions (e.g. exchangeable observ…
A discrete time event-history approach to informative drop-out in multivariate latent Markov models with covariates
Francesco Bartolucci, Alessio Farcomeni
Latent Markov (LM) models represent an important tool of analysis of longitudinal data when response variables are affected by time-varying unobserved heterogeneity, which is accou…
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…
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…
Bayesian inference through encompassing priors and importance sampling for a class of marginal models for categorical data
Francesco Bartolucci, Luisa Scaccia, Alessio Farcomeni
We develop a Bayesian approach for selecting the model which is the most supported by the data within a class of marginal models for categorical variables formulated through equali…
A note on the application of the Oakes' identity to obtain the observed information matrix of hidden Markov models
F. Bartolucci, A. Farcomeni, F. Pennoni
We derive the observed information matrix of hidden Markov models by the application of the Oakes (1999)'s identity. The method only requires the first derivative of the forward-ba…