11 citations · 12 across the 6 of their papers we have counts for
6 papers
Penalized Likelihood Optimization for Adaptive Neighborhood Clustering in Time-to-Event Data with Group-Level Heterogeneity
Alessandra Ragni, Lara Cavinato, Francesca Ieva
The identification of patient subgroups with comparable event-risk dynamics plays a key role in supporting informed decision-making in clinical research. In such settings, it is im…
TimeDepFrail: Time-Dependent Shared Frailty Cox Models in R
Alessandra Ragni, Giulia Romani, Chiara Masci
This paper introduces TimeDepFrail, an R package designed to implement time-varying shared frailty models by extending the traditional shared frailty Cox model to allow the frailty…
Nonparametric estimation of the Patient Weighted While-Alive Estimand
Alessandra Ragni, Torben Martinussen, Thomas Scheike
In clinical trials with recurrent events, such as repeated hospitalizations terminating with death, it is important to consider the patient events overall history for a thorough as…
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…
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…
Imaging-based representation and stratification of intra-tumor Heterogeneity via tree-edit distance
Lara Cavinato, Matteo Pegoraro, Alessandra Ragni +3
Personalized medicine is the future of medical practice. In oncology, tumor heterogeneity assessment represents a pivotal step for effective treatment planning and prognosis predic…