Number of sessions: 4
Hours per session: 4
- free for PhD candidates of the Graduate School
- €475,- for non-members
- Consult our enrolment policy for more information.
This course introduces the principles of quantitative comparative research. The course focuses on the practical aspects of accessing and utilizing tools for comparative research and the replication and critical assessment of published comparative studies.
There are four sessions of four hours. Sessions include a mix of lectures, discussion, presentations, in-class exercises, and student’s reflecting on the relevance of the course material for their own research. After each session, students will be asked to complete a short exercise reflecting on the material and the way it can contribute to their own research project.
After completion of the course participants will be able to:
- Understand the methodological and theoretical background and development of quantitative comparative research
- Design a comparative study that addresses a specific research question
- Employ comparative research methods in their own research
- Critically evaluate scientific studies using comparative methods
The course is useful for PhD students in all levels of their project who are new to the subject of comparative quantitative researchCandidates are recommended to bring their own data or their plans for data collection, but are not required to do so. At the minimum, students are expected to have thought about the comparative elements of their own research design in advance of the course.
Every session after the first one will draw on student’s assignments of +/- 300 words each, to be prepared in advance.
Background and resources
- The first session will begin with an overview of comparative research in different applications across social science disciplines.
- The second half will offer a guided tour of comparative methods resources, including data, online courses and materials.
- After the session, students will be asked to provide a 300 word description of their research project and research question, with specific attention for the comparative dimension.
Units, levels of measurement, and case selection
- This session will start with a reflection on the students’ research project and research questions, based on the assignment, which they prepared for session 2.
- The lecture part of the session dives into identifying and clarifying units and levels of measurement in comparative research
- The second half of the session will focus on case selection within comparative studies. We will do group exercises that challenge students to select an appropriate set of cases for selected research questions.
- After the session, students will be asked to write a brief report (300 words) in which they describe the measurement level(s) and data they intend to use in their research, and to reflect on the strengths and limitations of their choices.
- For this session students are asked to bring an example of previously published comparative research that they see as an example for their own research.
- The lecture part of the session contains a discussion of the strengths and weaknesses of comparative research designs
- The interactive part of the session contains an exercise in which students analyze the research examples they brought, including their strengths and weaknesses.
- After the session, students will be asked to provide a 300 word outline of their (envisaged) research design and a justification of the case selection in their own work
Data and implementation
- For this session students are asked to bring a laptop with SPSS and – if available – the data with which they plan to work.
- The session begins with a discussion of students’ assignments and general challenges in formulating a good research design.
- The lecture part of the final session will focus on issues of equivalence, comparability and data quality issues in a variety of social science disciplines.
- The second part of this session consists of a practical exercise in working with data. Participants may bring their own data. Students who do not have their own data yet can work with an example dataset provided by the instructor.
Bob Castelein is a PhD candidate in the department of Public Administration and Sociology and has been working at Erasmus University since 2016. His work focuses on the handling and transportation of refrigerated containers in seaports. Before joining Erasmus University, he completed masters in Economics & Business and History & International Relations at the University of Groningen. At Erasmus University he has taught Bachelor courses on quantitative methods, SPSS, and economics.