Objective: 1. The course introduces students to advanced statistical techniques for the analysis of quantitative data, in particular time series analysis and multilevel modeling.
Objective: 2. Students acquire practical data analysis skills by applying and using these techniques with quantitative data of their own choice.
Content: The aim of this course is to introduce students to advanced statistical techniques for the analysis of quantitative data that are frequently used in the literature of political science and public administration. The focus is specifically on explaining dynamic changes over time and how to account for contextual, macro-level effects on micro-level relationships. The techniques covered are aggregate and cross-sectional time series analysis and event history analysis as well as multilevel models.
Methods of instruction
Lectures, discussion, and assignments.
- Brandt, Patrick T., and John T. Williams. 2007. Multiple Time Series Models. Sage University Paper Series on Quantitative Applications in the Social Sciences, 07-148. Thousand Oaks, CA: Sage.
- Luke, Douglas A. 2004. Multilevel Modeling. Sage University Paper Series on Quantitative Applications in the Social Sciences, 07-143. Thousand Oaks, CA: Sage.
- Finch, W. Holmes, Jocelyn E. Bolin, and Ken Kelley. 2014. Multilevel Modeling Using R. Boca Raton, FL: CRC Press.
Recommended (4 chapters required):
- Box-Steffensmeier, Janet M., Henry E. Brady, and David Collier. 2008. The Oxford Handbook of Political Methodology. Oxford: Oxford University Press.
Additional readings (listed in course syllabus).
Assignments, research paper, and class participation.
Monday 27 October until 15 December, 13.00-15.00 hrs in 2B22 (except for 24 November and 8 December in room 5A19)