This is a five-day course on how to study dynamics in intensive longitudinal data, such as ambulatory assessments (AA), experience sampling method (ESM) data, ecological momentary assessments (EMA), real time data capture, observational data or electronic daily diaries. We provide a tour of diverse modeling approaches for such data and the philosophies behind them, as well as practical experience with these modeling techniques using different software packages (including R and Mplus).

This course is designed for researchers who are interested in gaining more insight in the diverse modeling approaches for intensive longitudinal data, with a specific focus on the underlying dynamics (i.e., lagged relationships). While there will be computer labs to obtain some hands-on experience, the emphasis in this course is on obtaining an overview of the diverse challenges associated with these data, and the different philosophies behind the techniques that have been designed to tackle these. 

For this course some knowledge of multilevel analysis and Bayesian statistics is preferable, but not required. Also, experience with R and/or Mplus is useful, but is not mandatory.