Qualitative comparative analysis (QCA): A mixed-method approach for studying complex causality

Introduction

Key terms: qualitative and quantitative research, complex causality, set-theory, fsQCA software package, introductory course, relevant for students in any PhD phase.

ECTS: 3 
Number of sessions: 5
Hours per session: 3.5

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, QCA is gaining prominence in various social sciences, including political science, economics and business, management, pedagogical sciences, health sciences, sociology, and environmental sciences.

The unique added value of QCA lies in its set-theoretic approach. By analysing the relationships among sets of cases, QCA facilitates a more nuanced and complex examination of causation than is afforded by other empirical methodologies.

The class meetings comprise lectures, group discussions and exercises, which are supported by videos that were made for our MOOC on the topic.

Please note that you will need a laptop in all sessions to make notes and assignments.

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 can be useful for researchers from all research disciplines, in any phases of a PhD trajectory. 

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.

QCA can be applied for both small samples (with at least 10 cases) and larger samples.

The course will be less useful for participants who have already completed our QCA MOOC.

Relations with other courses

 
There are no distinct relations and no significant overlap between this course and other courses offered by the EGSH.

Sessions and preparations

Session 1: The set-theoretic foundations of QCA and the first research steps
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 research model and the calibration.
Preparations: Study of videos from our MOOC

Session 2: The truth table and the process of logical minimisation
In session 2 we will discuss how to make a truth table in Crisp-set QCA (csQCA) and Fuzzy-set QCA (fsQCA), which are the two main QCA approaches. Once the truth table is made, it can be logically minimised, which is a process that amounts to a systematic comparison between cases. 
Preparations: Study of videos from our MOOC, and first exploration of empirical publications

Session 3: Reading the solution
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. 
Preparations: Study of videos from our MOOC

Session 4: Necessity, epistemology, and using QCA software
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. We will also reflect on the epistemology of causal claims in QCA, and practice how to use the software program called fsQCA.
Preparations: Study of worked example, installation of the program fsQCA 4.1

Session 5: Doing the write-up and evaluating QCA
In session 5, 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.
Preparation: Study of a video from our MOOC, preparation of a short report based on your own QCA