A tutorial for joint modeling of longitudinal and time-to-event data in R

In biostatistics and medical research, longitudinal data are often composed of repeated assessments a variable dichotomous indicators to mark an event interest. Consequently, joint modeling time-to-event has generated much interest in these disciplines over the previous decade. In behavioural sciences, too, we interested relating individual trajectories discrete events. Yet, is rarely applied sciences more generally. This tutorial presents overview general framework for data, fully illustrates its application context behavioral study with JMbayes R package. particular, discusses practical topics, such as model selection comparison, choice parameterization interpretation parameters. end, this aims at introducing didactically theory related introduce novice analysts use