Objectives
- Understand when to use single measurement, panel, and intensive time-series data- Explain the difference between within-subject effects and between-subject effects- Estimate vector-autoregression models from longitudinal data- Critically assess the interpretation from longitudinal data analyses- Understand the basics of multi-level analysis- Estimate personalized network models from single subject timeseries- Etimate multi-level network models from time-series data of multiple participants- Estimate network models from panel data- Incorporate latent variable and measurement errors in (longitudinal) network models
Who Should Attend
- Instructors of undergraduate and graduate level courses looking to set-up a course on Network Psychometrics at their institution- (Established) researchers looking to master new methodological skills- Clinical practitioners and other professionals in a similar role interested in expanding their research agendas- Mid-career professional looking to expand their data analytical training- Social scientists interested in analyzing multivariate datasets
Entry Requirements
There are no formal entry requirements. It would be beneficial if participants had some familiarity with R. However, even participants unfamiliar with this statistical software will be able to effectively participate in the course, as we will dedicate time to learn the basics of programming in R.
Lesson Delivery
The mode of delivery is face-to-face workshops with 4h teaching sessions (2 in the morning, 2 in the afternoon) and 3h practical/seminar style sessions (1.5 in the morning and 1.5 in the afternoon). During the last training day more time may be devoted to seminar-style teaching to allow participants to prepare their presentations.
