Background In clinical research, there is an increasing interest in joint modelling of
longitudinal and time-to-event data, since it reduces bias in parameter estimation and …

Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R,
SAS, and BUGS provides the reader with a practical introduction into the analysis of interval …

Type 1 diabetes (T1D) is a disease of insulin deficiency that results from autoimmune
destruction of pancreatic islet β cells. The exact cause of T1D remains unknown, although …

Background & aims High protein intake has been linked to increased type 2 diabetes (T2D)
risk. However, if this association differs by protein from specific food sources, and if a …

Unlike standard prediction tasks, survival analysis requires modeling right censored data,
which must be treated with care. While deep neural networks excel in traditional supervised …

Joint models initially dedicated to a single longitudinal marker and a single time‐to‐event
need to be extended to account for the rich longitudinal data of cohort studies. Multiple …

Introduction The association between a change in proteinuria over time and its impact on
kidney prognosis has not been analysed in complement component 3 (C3) glomerulopathy …

Objective To characterize how disease progression is associated with mortality in a large
cohort of patients with Parkinson disease (PD) with long-term follow-up after subthalamic …

Joint modelling of longitudinal and time-to-event data has received much attention recently.
Increasingly, extensions to standard joint modelling approaches are being proposed to …

Background Joint modelling of longitudinal and time-to-event outcomes has received
considerable attention over recent years. Commensurate with this has been a rise in …