C10 - Applied Multilevel Modelling - Kim Mannemar Sonderskov

Instructor Details

Kim Soenderskov

Aarhus Universitet

Course Number
Course Teacher
Kim Soenderskov
Aarhus Universitet
Teaching Assistant
Frederik Hjorth
University of Copenhagen

Short Outline
The course equips the students with a thorough understanding of multilevel modelling and its application to political science research. The course covers linear and logistic hierarchical models with fixed and random intercepts as well as random slopes. It also deals with non-hierarchal models such as crossed random effects and it will touch upon techniques to model time in multilevel modelling. The course is an applied course that focuses on how to analyse multilevel data using Stata and how to interpret the results. In the lectures and the lab sessions we will use examples and data from research in political science and discuss the applied estimation strategy and the results. By the end of the course the students will be able to analyse a variety of research questions using multilevel modelling and to interpret and report the results in accordance with widely accepted conventions. Prerequisite knowledge Note from the Academic Convenors to prospective participants: by registering to this course, you certify that you possess the prerequisite knowledge that is requested to be able to follow this course. The instructor will not teach again these prerequisite items. If you doubt whether you possess that knowledge to a sufficient extent, we suggest you contact the instructor before you proceed to your registration. Students must have a solid grasp of linear and dichotomous (logit/probit) regression analysis and the assumptions behinds these techniques. They must also be familiar with Stata (simple data management and analysis) and have a basic understanding of maximum likelihood estimation. The following books are useful refreshers on these issues. Achen, C.H. (1982). Interpreting and using regression. Sage Publishers. Berry, W.D. (1993). Understanding regression assumptions. Sage Publishers. Long, J.S., & J. Freese, (2006). Regression models for categorical dependent variables using Stata. Stata Press. Kohler, U., & F. Kreuter (2012). Data analysis using Stata. Third edition. Stata Press. Short Bio Kim Mannemar Sønderskov is an associate professor at the Department of Political Science, Aarhus University, Denmark, from which he also earned his PhD. His fields of interests include political behaviour and attitudes, neighbourhood effects, and economies of scale in public organizations. His works have appeared in European Sociological Review, Political Studies, Rationality and Society and Public Choice, among others. He has written a textbook on statistical analysis using Stata (in Danish, forthcoming in English), and has taught multiple courses on applied statistics at the BA, MA and PhD level.

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