5 papers
Asymmetric Laplace distribution regression model for fitting heterogeneous longitudinal response
Antoine Barbieri, Angelo Alcaraz, Mouna Abed +2
The systematic collection of longitudinal data is very common in practice, making mixed models widely used. Most developments around these models focus on modeling the mean traject…
A regularized multi-state model for covariate selection with interval-censored survival data
Ariane Bercu, Agathe Guilloux, Cécile Proust-Lima +1
In population-based cohorts, disease diagnoses are typically censored by intervals as made during scheduled follow-up visits. The exact disease onset time is thus unknown, and in t…
Dynamic prediction of an event using multiple longitudinal markers: a model averaging approach
Reza Hashemi, Taban Baghfalaki, Viviane Philipps +1
Dynamic event prediction, using joint modeling of survival time and longitudinal variables, is extremely useful in personalized medicine. However, the estimation of joint models in…
A Two-stage Joint Modeling Approach for Multiple Longitudinal Markers and Time-to-event Data
Taban Baghfalaki, Reza Hashemi, Catherine Helmer +1
Collecting multiple longitudinal measurements and time-to-event outcomes is a common practice in clinical and epidemiological studies, often focusing on exploring associations betw…
A Two-Stage Bayesian Approach for Variable Selection in Joint Modeling of Multiple Longitudinal Markers with Competing Risks
Taban Baghfalaki, Reza Hashemi, Christophe Tzourio +2
In many clinical and epidemiological studies, collecting longitudinal measurements together with time-to-event outcomes is essential. Accurately estimating the association between…