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Member rate 2,713.79 zł
Non-Member rate 5,427.58 zł
Save 221.03 zł Loyalty discount applied automatically*
Save 5% on each additional course booked
* If you attended a qualifying previous Methods School in 2025 or 2026, you qualify for 221.03 zł off your course fee.
Jagiellonian University: 8 – 11 September
Online: 14 – 15 September
This course introduces quantitative researchers to working with and analysing panel data, that is, data with repeated observations of the same unit (e.g. respondents or countries). The course begins with hands-on approaches to understanding and preparing longitudinal data, before moving to both basic and more advanced methods for panel data analysis.
Key topics include longitudinal data handling and description, visualisation, and panel data methods, from standard fixed- and random-effects models to recent developments in the difference-in-difference literature.
The course focuses on how these methods are used in existing academic research (especially political science and sociology) and how you can apply them to your own research questions.
During the course, you will explore real-world software examples based on existing panel datasets. By the end of the course, you will be able to choose between different research designs for your longitudinal data, apply longitudinal methods, and critically assess empirical studies using longitudinal data and methods.
Nadja Wehl is a postdoctoral researcher in Political Science at the Cluster of Excellence 'The Politics of Inequality' at the University of Konstanz. Her research focuses on socio-economic inequalities, political attitudes and behaviour, perceptions of inequality, and political socialisation. Her work also examines digital campaigning, with a particular emphasis on the role of data and algorithms in contemporary politics.
Nadja is involved in collecting a panel data set of German students and often publishes research based on longitudinal data in journals including Comparative Political Studies. She has extensive experience teaching quantitative methods, including teaching introductions to longitudinal/panel data and methods.
The course offers an introduction to panel data and methods. A central focus of the course is the differentiation between 'between-variance', i.e. differences between units, and 'within-variance', i.e. changes within one unit over time. We will discuss how to think about these two types of variance in panel data, how to describe and visualise them, and how to analyse them jointly or separately. Throughout the course, you will connect these issues to applications in existing publications and to your own research questions.
In particular, the course examines standard fixed-effects and random-effects models in the context of panel data, as well as 'hybrid' between-within models. It also considers threats to causality while discussing difference-in-difference and fixed effects with individual-specific slopes.
While the course covers some of the most important notations and formulas for panel data, as an introductory course, it aims to build an intuitive, not math-heavy, understanding of the methods presented.
Throughout the course, you will explore real-world applications of longitudinal data handling and analysis techniques in statistical software (R and Stata) based on existing panel (survey) datasets. Participants are encouraged to come with their own data. The last day is dedicated to supervised work with participants’ own data.
Handling of panel data (panel data structure, reshaping, merging, leads and lags, spells). Visualisation of panel data. Description of panel data.
Introduction, application, and examples of fixed effects and random effects estimation in panel data. Demeaning and first differences. Within and between estimation.
'Hybrid' between-within models; Interaction effects in panel data; two-way fixed effects models.
Introduction to difference-in-difference estimation; the parallel trends assumption; introduction to fixed effects with individual-specific slopes; introduction to recent advances of difference-in-difference estimation
Participants apply the course content to their own research questions and, ideally, their own panel (longitudinal) data.
The course is structured into five live sessions, each lasting three hours. The first three sessions will take place from Tuesday 8 – Thursday 10 September at Jagiellonian University in Kraków. The remaining two sessions will take place on Monday 14 and Tuesday 15 September, online. You must attend all sessions to complete the course.
The instructor will also conduct Q&A sessions and offer designated office hours for one-to-one consultations.
You are expected to have a basic understanding of research design and must be familiar with regression analyses in cross-sectional settings. Familiarity with statistical software (R, Stata, or similar) is also expected. No advanced statistical knowledge is required.
The course is designed at an introductory level.
You should expect approximately 20 hours of total engagement, including:
You will engage in a variety of activities designed to deepen your understanding of the subject matter. While daily live teaching sessions from the core of your learning experience, the learning commitment will extend beyond these. This ensures that you engage deeply with the course material, participate actively, and complete assessments to solidify your learning.
If you have registered and paid for the course, you will be given access to our Learning Management System (LMS) approximately two weeks before the course start date. Here, you can access course materials such as pre-course readings.
During the course week, participants are expected to commit time to preparing for each session, including readings and practical assignments.
This course description may be subject to subsequent adaptations (e.g. taking into account new developments in the field, participant demands, group size, etc.). Registered participants will be informed at the time of change.
By registering for this course, you confirm that you possess the knowledge required to follow it. The instructor will not teach these prerequisite items. If in doubt, please contact us before registering.