Dynamic Risk Predictions from Joint Models, with Applications in R
Dr. Dimitris Rizopoulos, Professor in Biostatistics
Erasmus University Medical Center
10am-1pm Eastern Time, March 9, 2023
Abstract: This workshop focuses on data collected in follow-up studies. Outcomes from these studies typically include longitudinally measured responses (e.g., biomarkers) and the time until an event of interest occurs (e.g., death, dropout). The aim often is to utilize the longitudinal information to predict the risk of the event. An important attribute of these predictions is that they have a time-dynamic nature, i.e., they are updated each time new longitudinal measurements are recorded. In this workshop, we will introduce the framework of joint models for longitudinal and time-to-event data and explain how it can be used to estimate and evaluate such dynamic risk predictions. We will use the R package JMbayes2 to showcase the capabilities of these models.
2023 Joint Statistical Meetings
The 2023 Joint Statistical Meetings will be August 5 - 10 in Toronto, Ontario. For more information, please visit the JSM webpage.