Introduction to Longitudinal Data Analysis

In this course you will learn both how to clean longitudinal data as well as the main statistical models used to analyse it. The course will cover three fundamental frameworks for analysing longitudinal data: multilevel modelling, structural equation modelling and event history analysis.

The course is organised as a mixture of lectures and hands-on practicals using real-world data. During the course, there will also be opportunities to discuss also how to apply these models in your own research.

Outcomes:

• To gain competence in the concepts, designs and terms of longitudinal research.
• To be able to apply a range of different methods for longitudinal data analysis.
• To have a general understanding of how each method represents different kinds of longitudinal processes.
• To be able to choose a design, a plausible model and an appropriate method of analysis for a range of research questions.

Topics covered by session

13.03.2025  – Data cleaning and visualization of longitudinal data

21.03.2025 – Cross-lagged models (covering also an introduction to Structural Equation Modelling and auto-regressive models)

28.03.2025 – Multilevel model of change (covering also an introduction to multilevel modelling)

04.04.2025 –  Latent Growth Modelling

11.04.2025  – Survival models (also known as event history analysis)