Course Objective
Students who have completed this tutorial will understand the principles and the uses of multilevel analysis and panel regression and they will be able to apply these methods in their own research question.Course Content
In social sciences we are often confronted with research entities clustered in different levels:sometimes we analyze pupils who are grouped within various classes and schools or we study patients that are treated by the same doctors or in the same hospitals. In this tutorial, we learn how to properly analyze these data and draw reliable conclusions for different levels of analysis. A particular type of these data that are often used in social sciences are panel data. In this data, we have repeated observations (typically in time) for the same individuals. We pay particular attention to the methods needed to analyze panel data as these allow us to correct for unobserved individual differences.
This tutorial begins with a general introduction to multilevel regression models for continuous variables. Then, we discuss the main concepts and issues in multilevel analysis. Then we proceed by introducing panel regression models and apply them in the context of social sciences. The practical work consists of meeting-specific exercises with applications of the material that is discussed in class. Students get real data from various datasets to practice with R. Finally, students are asked to work on real data themselves.
Teaching Methods
The course include four sessions on location. The sessions combine theory with exercises. Attendance is required for all sessions. Students are also expected to study chapters of the designated books. After the second session, students can start with the final assignmentMethod of Assessment
Written assignmentLiterature
Hox, J. J., Moerbeek, M., & van de Schoot, R. (2017). Multilevel Analysis: Techniques and Applications (Third). RoutledgeTarget Audience
Research Master in Social SciencesLanguage of Tuition
- English
Study type
- Master