Combining Dynamic Predictions From Joint Models for Longitudinal and Time-to-Event Data Using Bayesian Model Averaging

• Published in: Journal of the American Statistical Association Vol. 109; no. 508; pp. 1385 - 1397
• Main Authors: Rizopoulos, Dimitris, Hatfield, Laura A., Carlin, Bradley P., Takkenberg, Johanna J. M.
• Format: Journal Article
• Language: English
• Published: Alexandria Taylor & Francis 02.10.2014; Taylor & Francis Group, LLC; Taylor & Francis Ltd
• Subjects: Applications and Case Studies; Averaging; Bayesian analysis; Bayesian networks; Biomarkers; Datasets; Heart valves; Induced substructures; Mathematical models; Multilevel models; prediction; Predictive modeling; Probability; Prognostic modeling; Random effects; Real time; Reoperation; Risk assessment; Risk prediction; Simulations; Statistical models; Statistics; Time-dependent covariates

The joint modeling of longitudinal and time-to-event data is an active area of statistics research that has received a lot of attention in recent years. More recently, a new and attractive application of this type of model has been to obtain individualized predictions of survival probabilities and/o...