This training session is delivered by Dr Clemens Jarnach for the GUDTP
This four-hour workshop offers a practical introduction to panel and longitudinal data analysis (LDA) using R. Panel data—observations of the same individuals, organisations, or countries across multiple time points—are central to identifying causal relationships and accounting for unobserved factors in the social sciences.
The workshop introduces the core concepts and applied techniques of LDA, drawing on perspectives from sociology, econometrics, and data science. Participants will learn when LDA is appropriate, how to structure and prepare panel datasets, and how to implement common modelling approaches in R. Through short lectures, code demonstrations, and guided exercises, students will learn to work with Fixed Effects and Random Effects models, address unobserved heterogeneity, and choose suitable models for their own research.
The workshop covers:
- Fundamentals of panel data: definitions, when to use LDA, and essential data management strategies.
- Key longitudinal modelling approaches: handling unobserved heterogeneity, Fixed Effects and Random Effects models, model selection, and basic robustness checks.
- Applied examples and case studies illustrating LDA in practice.
Pre-requisites:
Participants should have a basic working knowledge of R for data manipulation and regression modelling, and be familiar with Ordinary Least Squares (OLS) regression and hypothesis testing.
Spaces are limited so we cannot guarantee a place at the point of registration. Places will be allocated on a first-come, first-served basis, and once places are full, we will maintain a waiting list.
Those allocated a place will be informed by e-mail
Booking will open in March 2026
