1 citations · 1 across the 5 of their papers we have counts for
5 papers
Cluster-weighted modeling of lifetime hierarchical data for profiling COVID-19 heart failure patients
Luca Caldera, Andrea Cappozzo, Chiara Masci +5
This study investigates the heterogeneity in survival times among COVID-19 patients with Heart Failure (HF) hospitalized in the Lombardy region of Italy during the pandemic. To add…
Analysis of Higher Education Dropouts Dynamics through Multilevel Functional Decomposition of Recurrent Events in Counting Processes
Alessandra Ragni, Chiara Masci, Anna Maria Paganoni
This paper analyzes the dynamics of higher education dropouts through an innovative approach that integrates recurrent events modeling and point process theory with functional data…
Uncover mortality patterns and hospital effects in COVID-19 heart failure patients: a novel Multilevel logistic cluster-weighted modeling approach
Luca Caldera, Chiara Masci, Andrea Cappozzo +4
Evaluating hospitals' performance and its relation to patients' characteristics is of utmost importance to ensure timely, effective, and optimal treatment. Such a matter is particu…
Joint modelling of recurrent and terminal events with discretely-distributed non-parametric frailty: application on re-hospitalizations and death in heart failure patients
Chiara Masci, Marta Spreafico, Francesca Ieva
In the context of clinical and biomedical studies, joint frailty models have been developed to study the joint temporal evolution of recurrent and terminal events, capturing both t…
Clustering Hierarchies via a Semi-Parametric Generalized Linear Mixed Model: a statistical significance-based approach
Alessandra Ragni, Chiara Masci, Francesca Ieva +1
We introduce a novel statistical significance-based approach for clustering hierarchical data using semi-parametric linear mixed-effects models designed for responses with laws in…