📈 Introducing Context: Multilevel modeling in Stata and R
This seminar gives an introduction to hierarchical structured data and teaches students how to do basic multilevel analyses with Stata or R. Using survey data from the European Values Study and the German Longitudinal Election Study, students will learn how to independently analyze political attitudes and behavior across contexts.
In the first half of the course, we will repeat the foundations of statistical analyses. We will recapitulate data manipulation as well as linear and logistic regression analyses. In the second half of the course, the focus will be on multilevel analyses. After a broad introduction into hierarchical structured data and its consequences for data analyses, students will learn how to apply different kinds of hierarchical regression models using applied examples. Here, the focus will be on fixed- and random-effects intercepts in analyses of cross-country and panel data.
Students will have to hand in weekly assignments in which they are asked to apply the contents of the course. At the end of the semester, students are required to write a short empirical research paper on a topic of their choosing, using multilevel analysis. As a prerequisite, Students are expected to bring a basic understanding of data analysis and the use of Stata or R. During the whole course, students can freely choose whether they prefer to work in Stata or R. While most of the in-lesson examples will be taught using Stata, all material will be made available in Stata and R.