This course will teach you to how conceive and conduct the most appropriate comparative research design – the latter broadly defined as any research enterprise that comprises at least two ‘cases’ or observations.
On the one hand, it will cover fundamental questions ‘upstream’ of practical and hands-on choices: what is comparison? Why compare; what is the added value of comparison? What are the logical underpinnings and mental operations behind comparison? What should be the mindset of a good comparative researcher? What should be his/her goals? What is the link between a research puzzle and the choice for a comparative research design? What would be the alternative(s)? Does one conceive and does one perform comparison in the same way when the ‘cases’ are situated at the micro (i.e. individuals), meso (e.g. organisations) or macro (e.g. political or policy systems) levels? Etc.
On the other hand, we will examine in detail the practicalities of different types of comparative research designs, by following all the hands-on steps: (1) prior arbitrations and ‘casing’, i.e. the definition of the cases; (2) case selection, through more basic or more advanced strategies; (3) collecting and managing comparative data; (4) comparative data analysis (qualitative, QCA and quantitative options). As explained below in detail, steps (1) and (2) will be examined in greater detail.
The course is organised in five sessions, each allowing time for open discussions and interaction.
After introducing the practical and organisational aspects of the course, we will frame comparative research in the broader context of a comparative approach. This means considering some epistemological issues underpinning comparison. Starting from the discussion of comparison as a basic mental operation, we will progress to comparison in the social sciences, then to political science specifically. One core focus will be on the different goals of comparison, with practical examples. To conclude, we will discuss a first series of participants’ projects, focusing on the goals pursued (why go for a comparative research design?).
We locate comparative research designs within the whole range of possible designs. We present the practical steps of a good comparative research design, focusing on the major arbitrations. We also have a first look at Step 1 operations that lie upstream of case selection, such as the formulation of the research question(s) and hypotheses, the correct use of concepts for the purpose of comparison, the number of cases one will be able to manage, and the choice between cross-country or within-country case selection. We conclude by discussing a second series of participants’ projects, with a focus on upstream arbitrations.
We continue examining Step 1 operations, and deepen the question of 'what is a case?' within a comparative research design – with an emphasis on core arbitrations such as depth vs breadth and cross-country vs within-country vs within-system casing and case selection. Then we’ll systematically survey all the main options for the core Step 2 operation: case selection. We first envisage rather basic or simple strategies of case selection, from very small-N to very large-N, and following different criteria; the pros and cons of each strategy will also be discussed. We conclude by discussing a second series of participants’ projects, with a focus on casing and case selection
We turn to more refined strategies, in particular considering time/sequence and multilevel phenomena, and discussing the pros and cons of each. Then we look at hands-on tricks of the trade for collecting and managing data in a comparative research (Step 3) – including ways to troubleshoot and to make case selection adjustments as your research develops. A fourth interactive section around participants’ projects will focus on case selection and data collection/management.
We examine different ways to engage in comparative data analysis, envisaging three main families of options:
- case-oriented (or ‘qualitative’) analyses
- Qualitative Comparative Analysis (QCA) for systematic cross-case comparison
- statistical/’quantitative’ analyses.
We will examine the pros and cons of each, as well as the potential difficulties of sequencing different data analysis techniques in a mixed- or multi-method design. In particular, we'll discuss the potential of sequencing QCA with single case studies, in small- or intermediate-N designs. In the second part of the morning session, we revisit some core points – with a focus on the strengths of comparative research designs, but even more on main perils or caveats of comparison. You will become more aware of ways to 'mis-compare' – and avoid it in your own research.
Finally, in an open interactive session, we'll discuss points still to be clarified, points of debate or disagreements, remaining questions and answers about participants’ projects, etc.
You are encouraged to bring your own research questions and hypotheses, first thoughts and difficulties (if any) in case definition and case selection, and (if applicable) any data you have already compiled. The course is designed to help you make the most appropriate choices in comparative research design. You will be able to reflect and to work on your own project as we follow the sequence of fundamental and then applied steps. Whenever possible, we’ll use input from participants’ own projects during the interactive parts of each one of the five sessions.
Connections with other courses (see also section 13 below):
- This course can be taken as a standalone course, but it has been designed as an introductory course, particularly for Summer School courses – in particular Methodologies of Case Studies, QCA and Fuzzy Sets and Mixed Methods Designs (exact course titles may change).
- This is not a specialist QCA course. Some main features of QCA (as an approach & set of techniques) will be presented at introductory level, but if you want hands-on QCA training, follow Eva Thomann's week-long Introduction to QCA course, or the two-week QCA course at the Summer School.
- The course may also be of interest for scholars engaged in ‘thick’ observational work (e.g. ethnography, participant observation, interviews, …) or in in-depth single case studies (using e.g. process tracing), as well as those interested in formalised or statistical approaches (large-N statistical techniques, experiments, …), especially if their populations and/or samples are not so obvious to circumscribe.