Introduction
Course information
Key terms: Qualitative and quantitative research; Complex causality; fsQCA 4.1 software package; introductory course; relevant for students in any PhD phase.
ECTS: 2.5
Number of sessions: 4
Hours per session: 4
Course fee:
- free for PhD candidates of the Graduate School
- € 575,- for non-members
- consult our enrolment policy for more information
Aims and focus
Need to analyse cause-effect relations across multiple cases and not sure how? Qualitative Comparative Analysis (QCA) offers a systematic, transparent, and innovative solution.
Introduced by Charles Ragin in the 1980s and developed further since, QCA is gaining prominence in various social sciences, including political science, economics and business, management, pedagogical sciences, health sciences, sociology, and environmental sciences.
QCA is relevant for researchers who normally work with qualitative methods and are looking for a more systematic way of comparing and assessing cases. QCA is also useful for quantitative researchers who like to assess alternative (more complex) aspects of causation, such as how factors work together in producing an effect.
The class meetings comprise lectures, group discussions and exercises, which are supported by videos that were made for our MOOC on the topic (https://www.coursera.org/learn/qualitative-comparative-analysisOpens external). The course will be less useful for participants who have already completed our MOOC.
Please note that you will need a laptop in all 4 sessions to make notes and assignments.
Key Facts & Figures
- Type
- Course
- Instruction language
- English
What will you achieve?
- After completing the course you will know how QCA has historically developed and in which academic context.
- After the course you will know how a QCA study can be designed, under which conditions, and for what purposes.
- After completing the course you will know how to conduct a QCA study and understand the precise logics on which the analyses are based.
- After the course you know how to interpret and report the results of a QCA study.
Start dates
Session 1
April 1 (Tuesday) 2025
13.00-17.00 hrs
Mandeville building (campus map), room T19-01
Session 2
April 9 (Wednesday) 2025
13.00-17.00 hrs
Mandeville building (campus map), room T19-01
Session 3
April 15 (Tuesday) 2025
13.00-17.00 hrs
Mandeville building (campus map), room T19-01
Session 4
April 22 (Tuesday) 2025
13.00-17.00 hrs
Mandeville building (campus map), room T19-01
Entry level and relevance
This is an introductory course. It is designed for people who have no or limited experience with QCA. No prior knowledge or research experience is required.
The course is useful for researchers in all phases of their PhD trajectory.
QCA can help both quantitatively and qualitatively oriented researchers, and it can be applied for both small samples (with at least 10 cases) and larger samples.
There are no distinct relations and no significant overlap between this course and other courses offered by the EGSH.
Sessions and preparation
In the first session we will discuss the set-theoretic foundations on which QCA is based. We will also discuss the first research steps in QCA, which comprise designing a model, the calibration, and making a truth table. We will focus on making a truth table in Crisp-set QCA (csQCA), which is one of the two main forms of doing QCA.
Preparations: Study of videos from our MOOC
In session 2 we will discuss how to make a truth table in Fuzzy-set QCA (fsQCA), which is the second main QCA approach (next to csQCA). Once the truth table is made, it can be logically minimised, which is a process that amounts to a systematic comparison between cases. We will discuss the logic on which the process of minimisation is based and the meaning of its product, which is the minimal formula.
Preparations: Study of videos from our MOOC, and first exploration of empirical publications
In session 3 we will discuss how to interpret and evaluate the minimal formula that is obtained by the logical minimisation of the truth table. We will particularly discuss the meaning and the calculation of the parameters of fit of consistency and coverage, and reflect on the epistemology of causal claims in QCA. We will also discuss and practice how to use the software program called fsQCA.
Preparations: Study of videos from our MOOC; installation of the program fsQCA 4.1
In session 4 we will discuss the notion of necessity. A condition or combination of conditions is necessary for the outcome if the outcome needs it to occur. Further, we will discuss the write-up of a QCA study and you will be asked to reflect on the results of a QCA that you do for your own model. Lastly, we will have a critical reflection on the method.
Preparations: Study of videos from our MOOC; study of worked examples; preparation of a short report based on your own QCA.
About the instructor
Dr. Fadi Hirzalla is the Graduate School senior lecturer and methodology consultant. He specialises in quantitative and qualitative methods and methodology, next to his substantive interests in citizenship and new media, with a particular focus on intercultural relations and young people. Prior to joining the Graduate School, he worked at the University of Amsterdam and Utrecht University.
Contact
- Enrolment-related questions: enrolment@egsh.eur.nl
- Course content-related questions: hirzalla@egsh.eur.nl
- Telephone: +31 (0)10 4082607 (Graduate School).
Facts & Figures
- Fee
- free for PhD candidates of the Graduate School
- € 575,- for non-members
- consult our enrolment policy for more information
- Tax
- Not applicable
- Offered by
- Erasmus Graduate School of Social Sciences and the Humanities
- Course type
- Course
- Instruction language
- English