3 papers
stat.ME2025
A Bayesian joint model of multiple longitudinal and categorical outcomes with application to multiple myeloma using permutation-based variable importance
Danilo Alvares, Jessica K. Barrett, François Mercier +5
Joint models have proven to be an effective approach for uncovering potentially hidden connections between various types of outcomes, mainly continuous, time-to-event, and binary.…
stat.AP2024
A Bayesian joint model of multiple nonlinear longitudinal and competing risks outcomes for dynamic prediction in multiple myeloma: joint estimation and corrected two-stage approaches
Danilo Alvares, Jessica K. Barrett, François Mercier +5
Predicting cancer-associated clinical events is challenging in oncology. In Multiple Myeloma (MM), a cancer of plasma cells, disease progression is determined by changes in biomark…
stat.ME2024
Bayesian shared parameter joint models for heterogeneous populations
Sida Chen, Danilo Alvares, Marco Palma +1
Joint models (JMs) for longitudinal and time-to-event data are an important class of biostatistical models in health and medical research. When the study population consists of het…