Qualitative Comparative Analysis (QCA): Performing Basics and Advanced Analyses using R (CIVICA course)

Course Description: 
This is a methodological course on set-theoretic methods for the social sciences. It's a PhD level course open to doctoral students enrolled in a CIVICA institution, and MA students from International Relations, Public Policy and Political Science at CEU. In the registration, priority will be given to PhD students.

While the spectrum of a set-theoretic methods is broad, including techniques such as Mill’s methods or typological theory, this course primarily focuses on the crisp-set and fuzzy-set versions of Qualitative Comparative Analysis (QCA). Invented by Charles Ragin [1987], this technique is still undergoing modifications, improvements, and ramifications. These methods are applied in fields as diverse as political science, public policy, international relations, sociology, business, and management studies, or even musicology (see compasss.org). This course aims at enabling students to produce a publishable QCA of their own. In order to achieve this, this course provides both the formal set theoretical underpinnings of QCA and the technical and research practical skills necessary for performing a QCA. All applied parts of the course will be performed in the R software environment, using RStudio (Cloud). 
Core readings and software Schneider and Wagemann [2012] and Oana et al. [2021]. Students who wish to take the course and need more information as to what the course is about are invited to skim through the first chapters of these books. From the beginning, we will use specialized software for performing the analytic steps learned in class. We will use R [R Core Team, 2020] and RStudio [RStudio Team, 2020] and within it, the packages QCA [Dusa, 2018] and SetMethods [Oana and Schneider, 2018]. 
Learning Outcomes: 

Participants will not only increase their proficiency in R, but will also engage into discussions on more general methodological issues of good comparative research, such as principles and practices of case selection, concept formation, measurement validity, and forms of causal relations.

Course structure / We start with some basics of formal logic and set theory. Then we introduce the notions of sets and how they are calibrated. After this, we move on to the concepts of causal complexity and of necessity and sufficiency, show how the latter denote subset relations, and then learn how such subset relations can be analyzed with so-called truth tables. We learn how to logically minimize truth tables and what the options for the treatment of so-called logical remainders are. Once students master the current standard analysis practice, we discuss several extensions and possible improvements of QCA. Depending on the needs and interests of participants, we choose several topics from the following list: set-theoretic multi-method research, i.e. the combination of QCA with follow-up within-case analyses; the integration of time into QCA; theory-evaluation in set-theoretic methods; or QCAspecific procedures for robustness tests. 


Participation during synchronous meetings, including R coding exercises 20%
Engagement with readings on Perusall 10%
Quizzes 20%
Homework R coding assignments 5%
Final paper 45%


Since this is an advanced PhD course, students who plan to attend should first check for themselves and, in case of doubt, with Prof. Schneider whether they fulfill the following requirements: Participants should have (a) some practical experience in empirical comparative social research; (b) undergone some thorough courses in basic research methodology; and (c) preferably some basic statistical training, or at least hands-on knowledge with some sort of spreadsheet programs (even if it is just Excel).