Qualitative Comparative Analysis
Prerequisites (knowledge of topic)
Students should have previous exposure to social research methods, including basic training in quantitative methods, at the post-baccalaureate level.
Laptop (PC or Mac): Students should bring a laptop. The course will include instruction in the use of the software package fsQCA (for both Windows and Mac).
Please install the fsQCA software package ahead of the course. It can be please download for free at fsqca.com
Qualitative comparative analysis (QCA) is a research approach consisting of both an analytical technique and a conceptual perspective for researchers interested in studying configurational phenomena. QCA is particularly appropriate for the analysis of causally complex phenomena marked by multiple, conjunctural causation where multiple causes combine to bring about outcomes in complex ways.
QCA was developed in the 1980s by Charles Ragin, a sociologist and political scientist, as an alternative comparative approach that lies midway between the primarily qualitative, case-oriented approach and the primarily quantitative, variable-oriented approach, with the goal of bridging both by combining their advantages and tackling situations where causality is complex and conjunctural. QCA uses Boolean algebra for the analysis of set relations and allows researchers to formally analyze patterns of necessity and sufficiency regarding outcomes of interest. Since its inception, QCA has developed into a broad set of techniques that share their set-analytic nature and include both descriptive and inferential techniques.
Many researchers have drawn on QCA because it offers a means to systematically analyze data sets with only few observations. In fact, QCA was originally applied to small-n situations of between 10 and 50 cases; situations where there are frequently too many cases to pursue a classical qualitative approach but too few cases for conventional statistical analysis. However, more recently, researchers have also applied QCA to medium- and large-n situations marked by hundreds of thousands of cases. While these applications require some changes to how QCA is applied, they retain many advantages for analyzing situations that are configurational in nature and marked by causal complexity.
The goal of this workshop is to provide a ground-up introduction to Qualitative
Comparative Analysis (QCA) and fuzzy sets. Participants will get intensive
instruction and hands-on experience with the fsQCA software package and on
completion should be prepared to design and execute research projects using the
After successful completion of you should be able to:
1. understand the goals, assumptions, and key concepts of QCA
2. conduct data analysis using the fsQCA software package
3. design and execute research projects using a set-analytic approach
4. apply advanced forms of set-analytic investigation
I would like this workshop to be as useful to you as possible. To get the most out of this workshop, you would ideally already be working on an empirical project that might be aided by taking a configurational approach, but that is not essential. Over the course of this workshop, I hope you will be thinking about how you can apply these methods to your research, and I will do my best to be of assistance.
See below under structure
Day 1: Units 1-3
Day 2: Units 3-4
Day 3: Units 5-6
Day 4: Units 6-7
Day 5: Student Presentations
Unit 1. Introduction to the Comparative Method
The goal of this first unit is to offer an introduction to the logic of comparative research, as this perspective will be fundamental in informing our thinking for the coming days. The focus is on understanding social research from a set-analytic perspective as well as examining the distinctive place of configurational and comparative research.
Ragin, 2008 (“Redesigning Social Inquiry”): Chapters 1-2
Unit 2. The Basics of QCA
We’ll move on to the basics of QCA. We will begin with an Introduction to Boolean algebra and set-analytic methods. Other issues we will cover include set-analytic analysis vs. correlational analysis, the concepts of necessity and sufficiency as well as consistency, coverage, and set coincidence. Time permitting, we will also examine case-oriented research strategies for theory building.
Ragin, 2000: Chapters 3-5
Ragin, 2008: Chapters 1-3
Unit 3. Crisp Set Analysis
In this unit, we will dive into crisp-set QCA (csQCA), the simpler version of QCA using binary data sets. This will include the coding of data, the construction of truth tables, and understanding the three solutions—complex, parsimonious, and intermediate. We will also begin to examine the importance of counterfactual analysis based on easy versus difficult counterfactuals. Topics also include understanding consistency and coverage in crisp-set truth table analysis.
Ragin, 2000: Chapters 3-5
Unit 4. Fuzzy Set Analysis I
Fuzzy set analysis presents a slightly more complex version of QCA. We will start with the notions of fuzzy sets and fuzzy set relations before moving on to calibrating fuzzy sets and fuzzy set consistency, coverage, and coincidence.
Ragin, 2008: Chapters 4-5
Unit 5. The Fuzzy-Set Truth Table Algorithm
We will next cover the fuzzy-set truth table algorithm. Building on crisp set analysis, we will further examine issues around limited diversity, fuzzy sets and counterfactual analysis. We also will work with sample data sets.
Unit 6. Advanced Topics in QCA
This unit provides us with an opportunity to catch up and delve deeper into some of the topics introduced above. Should we feel comfortable enough, we will move on to some more advanced topics in QCA, including the testing of causal recipes and substitutable causal conditions.
Ragin, 2008: Chapters 7-10
Unit 7. Large-N Applications of QCA
The last unit will provide examples of recent large-N applications of QCA. These examples will give us an opportunity to raise further questions about how to execute research using a set-analytic approach. We will also reserve some time for further questions that have come up during the workshop.
There are four key books for the course, and required chapters are posted here in pdf format. I recommend reading the remainder of the books, but this is not required.
Ragin, Charles C. 1987. The Comparative Method: Moving beyond Qualitative and Quantitative Strategies. Berkeley, CA: University of California Press
Ragin, Charles C. 2000. Fuzzy Set Social Science. Chicago, IL: University of Chicago Press.
Ragin, Charles C. 2008. Redesigning Social Inquiry: Fuzzy-Sets and Beyond. Chicago, IL: University of Chicago Press.
Ragin, Charles, C., and Fiss, Peer C. 2017. Intersectional Inequality: Race, Class, Test Scores, and Poverty. Chicago, IL: University of Chicago Press.
Supplementary / voluntary
Goertz, Gary. 2006. Social Science Concepts: A User’s Guide. Princeton, NJ: Princeton University Press.
Goertz, Gary and James Mahoney. 2012. A Tale of Two Cultures: Qualitative and Quantitative Research in the Social Sciences. Princeton, NJ: Princeton University Press.
Rihoux, Benoit and Charles C. Ragin (eds.) 2008. Configurational Comparative Methods. Thousand Oaks, CA: Sage.
Schneider, Carsten and Claudius Wagemann. 2012. Set-Theoretic Methods for the Social Sciences: A Guide to QCA. New York: Cambridge.
Mandatory readings before course start
The above chapters.
Presentation (individual) (50%)
Research proposal written at home (individual) (50%)
To get inspiration for research proposals, I recommend that participants review recent research projects in their field using QCA. A bibliography of such projects is available at http://compasss.org/bibliography/
The “structure” section above presents a complete list of topics relevant to the examination. Specifically, the oral presentation and subsequent examination paper will focus on using course materials to develop a research proposal.
Examination relevant literature
All required chapters listed above are part of the examination relevant literature, as are all course materials such as PPTs and additional materials distributed to the participants during the course.