In this research placement, we will focus on statistical methods available for the analysis of cross-national differences. We will first discuss the challenges and limitations of quantitative cross-national comparative research. We will then learn four analytical strategies: (1) Cluster-Robust Standard Errors; (2) Separate model for each country; (3) Country Fixed Effects Model and (4) Country Random Effects Model. Students will be able to deepen their knowledge of each analytical strategy with a practical application with STATA based on the European Social Survey (Round 9). In the second part of the seminar, students will carry out their own research project by analysing cross-national data from the European Social Survey with STATA. The aims of this research placement are: (1) to understand the challenges of cross-national comparative analysis; (2) to get to learn statistical methods for cross-national comparative analysis; (3) to conduct cross-national comparative analysis with own research question based on the ESS data and (4) to interpret and present own statistical results. Please note: Basic knowledge of applied statistics and of STATA is a prerequisite for participation and indispensable for the successful completion of the course. close

• Andreß, HJ., Fetchenhauer, D. & Meulemann, H. Cross-National Comparative Research—Analytical Strategies, Results, and Explanations. Köln Z Soziol 71, 1–28 (2019).
• Bryan, M. & Jenkins, S. (2016): Multilevel modelling of country effects: A cautionary tale, ESR, 32, 3-22.
• Schmidt-Catran, A.W., Fairbrother, M. & Andreß, HJ. Multilevel Models for the Analysis of Comparative Survey Data: Common Problems and Some Solutions. Köln Z Soziol 71, 99–128 (2019).
close