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ECPR Winter School: Comparative Research Design
March 15, 2021 - March 19, 2021
£465 – £485This course provides training on methods that enable a researcher to construct a solid and well-argued comparative research design (CRD) – any research enterprise that comprises at least two ‘cases’ or units of analysis.
We will cover multiple options, from very few cases (small-n) to multiple cases (intermediate-n) to many cases (larger-n), and in particular options that are QCA-compatible.
By the end of this course, you will be able to write up a well-constructed CRD section for your project and to reflect strategically on your comparative research project.
Key topics covered
We will cover a logical sequence of topics that constitute the core building blocks of a solid CRD:
- Thinking upstream: why go comparative? What is the added value of comparison? What should be the mindset of a good comparative researcher? What is the link between a research puzzle and the choice for a CRD? How to formulate a comparative research question?
- ‘Casing’ operations: what are my cases, how to define them, conceptually and empirically? At which level(s) (micro, meso, macro) can they be apprehended? And what about the time dimension?
- Which case selection strategy to choose? How many cases and which ones? Should I go ‘smaller-n’ or ‘larger-n’? Should I select cases with similar or different outcomes? Which basic case selection strategies are available, and what are the pros and cons? And what about more advanced strategies, e.g. ‘nested’ (multilevel) designs, designs including multiple time periods, etc?
- How to systematically collect good-quality data when covering multiple cases? What are the tricks of the trade? How to gain sufficient ‘intimacy’ with the respective cases (case-based-knowledge)? And how to compile and manage this data?
- How to engage in comparative data analysis? Which toolbox(es) to select, among ‘qualitative’ (case-oriented), specifically comparative (in particular QCA – Qualitative Comparative Analysis), and ‘quantitative’ (statistical, variable-oriented) data analysis techniques?
We’ll unpack topics 1, 2 and 3 in detail, and take a bird’s eye view of topics 4 and 5 because they refer to multiple methods and techniques (including QCA).
This seminar-type course provides a highly interactive online teaching and learning environment, using state of the art online pedagogical tools. It is designed for a demanding audience (researchers, professional analysts, advanced students) and capped at a maximum of 12 participants so that the Instructor can cater to the specific needs of each individual.
Prerequisite Knowledge
Little prior knowledge is expected. Any training in qualitative and/or quantitative methods would be an asset, but is by no means a requirement. You should simply be willing to reflect openly about your research design – there is no ‘best’ or ‘one-size-fits-all’ comparative research design.