Pillar 3: Methods
Qualitative and quantitative methods in public administration research will form an important part of the curriculum.
- Qualitative and Quantitative Research Methods of Public Administration and Research Design (Methods I) (first semester)
This course provides students with an overview of research methods in the social sciences, with a specific focus on administrative studies. Epistemological debates about how and why we do research are explored as well as issues of causation and data collection. Regarding qualitative methods, case study design, comparative historical methods, discourse analysis (also computer-based), surveys as well as interview techniques are discussed. The survey of quantitative methods includes descriptive statistics, regression analysis and QCA. Particular emphasis is placed on innovative combinations of research methods. The final part of the course focuses on the ethical dimensions of social science research. Doctoral researchers are encouraged to reflect on the epistemological as well as methodological challenges of their own their thesis projects.
- Advanced Research Methods for Public Administration and Research Design (Methods II) (second semester)
As the majority of doctoral researchers are expected to carry out field research on particular administrations, this class focuses, in particular, on interview techniques (structured, semi-structured, open, narrative), methods of interpretation, the organization of field research as well as the participatory observation. Comparative case study design, case selection and network analysis are also central. Doctoral researchers are expected to use cases and analytical puzzles from their own work, so that the class is instrumental in developing a proper research design for the respective theses.
- Quantitative Methods (optional) (Methods III) (third and fourth semesters).
This course is optional, as not all PhD students require an advanced understanding of quantitative methods. Those whose work requires quantitative methods are expected to undertake practical work on their theses in the course using advanced regression analysis (Pooled Time-Series Regression), factor and cluster analysis or QCA. Methodological tools like Stata, SPSS, and R are also introduced.
Doctoral researchers have the choice to take this course in the third or fourth semester to allow for some flexibility.