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Introduction to Qualitative Comparative Analysis (QCA)

Course Dates and Times

Monday 25 February – Friday 1 March, 09:00–12:30
15 hours over five days

Eva Thomann

eva.thomann@uni-konstanz.de

Institution: Universität Konstanz

This course introduces you to crisp set and fuzzy set Qualitative Comparative Analysis (QCA) and its analysis in R using the interactive graphical interface of the package QCA. It will give you a basic understanding of the analytic underpinnings and steps of QCA, and enable you to independently perform a basic crisp or fuzzy set QCA (Standard Analysis).

We will look at the origins, analytic aims, and variants of QCA and deal in depth with techniques and practices of set calibration. The nuts and bolts the QCA technique, from parameters of fit to all steps of the analyses of necessity and sufficiency, are illustrated based on an empirical example study which we replicate in class. We will then cover the presentation and interpretation of QCA results, as well as ways to deal with limited diversity and other potential pitfalls. Hands-on exercises and daily lab sessions provide opportunities for practice and engagement.

Tasks for ECTS Credits

2 credits (pass/fail grade) Attend 90% of the course hours, participate fully in in-class activities, and carry out the necessary reading and/or other work prior to, and after, class. Daily assignments will be either solutions to exercises provided after each lesson (to be submitted in Word format or equivalent), or solutions to R exercises (to be submitted as R script file).

4 credits As above, plus complete a take-home paper. The paper (2500–4000 words, excluding title page, references and appendices) will consist of one of the following:

a replication of a published QCA study (necessity and Standard Analysis)
a QCA (necessity and Standard Analysis) based on participants’ own data
(only after consulting with the instructor) a critical reflection of/epistemological engagement with methodological, QCA-related aspects of your own projects or a published study.

In case of the former two, you will need to submit the paper (in Word or equivalent) and the separate R script documenting your analysis. Submission deadline [tbc].

More information about assignments will be provided in class. You will be provided with a list of applied QCA studies from different disciplines for inspiration.

Instructor Bio

Eva Thomann is a Senior Lecturer at the Department of Politics of the University of Exeter who specialises in Public Policy and Public Administration. Previously she held research positions at the University of Bern, the Mannheim Centre for European Social Research, the University of Heidelberg, and the European University Institute in Florence.

Eva is the first author of Designing Research with Qualitative Comparative Analysis (QCA). and the award-winning monograph Customized implementation of European Union food safety policy: United in diversity?

She has published extensively on case-oriented and set-theoretic research methods, policy implementation, and Europeanisation using innovative case-oriented and set-theoretic methodology such as Enhanced Standard Analysis, formal set-theoretic theory evaluation, robustness tests, large-N QCA, congruence analysis, explanatory typologies, and Comparative Multilevel Analysis.

Eva Thomann teaches case-oriented and set-theoretic methods at doctoral schools, invited workshops, and at MA level. She serves in various international networks and contributes to the development of pedagogical resources and other innovations in the use and teaching of QCA. See her personal website

@EvaThomann

This course introduces you to crisp set and fuzzy set Qualitative Comparative Analysis and its analysis in R using the interactive graphical interface of the package QCA. It will give you a basic understanding of the analytic underpinnings and steps of QCA and enable you to independently perform a basic crisp or fuzzy set QCA (Standard Analysis). Hands-on exercises and daily lab sessions provide opportunities for practice and engagement.

Depending on how many ECTS points you want, you can engage in a blend of 'manual' exercises (e.g. calibrating sets, Boolean algebra, crisp-set QCA) and R assignments, for which solutions will either be provided or discussed in the next lab session. At the end of the course, you will:

Be able to correctly identify the suitable use, variant of, and approach to QCA for answering your research question
Be familiar with approaches to and issues of set calibration
Have a solid understanding of the logical and technical underpinnings of QCA
Be familiar with a selection of classic and recent key readings about QCA
Be able to independently carry out an analysis of necessity and sufficiency (Standard Analysis) with crisp and fuzzy sets, with the shiny GUI app of the R package QCA, visualise the results, and document your analysis
Be able to understand and interpret the results of a QCA, and assess the quality of a QCA study
Have a basic understanding of potential pitfalls when drawing inferences with QCA, and ways to address them.

The course presupposes the knowledge and skills taught in short course WA102, Foundations of set-theoretic and case-oriented thinking and methodology. It will not cover advanced analytic tools such as Enhanced Standard Analysis, theory evaluation, or set-theoretic multi-method analysis. To learn these more advanced features, we recommend you follow this course up with the second week of the Qualitative Comparative Analysis and Fuzzy Sets course at our 2019 Summer School in Budapest and the Advanced Topics in Set-Theoretic Methods and QCA course at our 2020 Winter Methods School in Bamberg.

While we will use the R packages QCA (and, where warranted, SetMethods), we will not be working primarily with command lines offering the most advanced functionality for QCA software. Instead we employ the user-friendly, interactive graphical interface (shiny GUI app), which offers more basic functionality. We will, however, document our work in R scripts and occasionally discuss how to interpret and work with R commands. As such, the course teaches an 'easy' way to perform QCA with R, with its own limitations. You will gain basic familiarity with R and be able to transparently document your analysis for replication. However, to gain full proficiency in R, you will need further training or self study.

Day one
We look at the origins, analytic aims, and variants of QCA, and deal in depth with techniques and practices of set calibration. We discuss the distinction between QCA as a technique and QCA as an approach, and what that implies for designing research and taking analytic decisions. The lab session serves two purposes: to get familiar and play around with the graphical interface of the shiny GUI app, and to briefly refresh, deepen and practice the contents on causal complexity, INUS causation, and Boolean algebra.

Day two
We introduce the technical underpinnings of QCA, and discuss how to calculate the membership of cases in sets and complex combinations of sets (such as truth table rows or solution terms). We look at the meaning and calculation of two main parameters of fit with QCA: consistency and coverage. By ways of XY plots, we will learn how to assess fuzzy set relations of necessity and sufficiency using these criteria. The lab session covers set calibration, combining sets, and producing nice graphs – XY plots and Venn diagrams – with R.

Day three
We do our own basic QCA, looking first at all steps of the analyses of necessity and sufficiency, explained with the example of an empirical study. We look briefly at the implications of skewed set membership for these analytic steps. In the lab session, you will do your own first crisp set QCA by hand. Using R, we will then analyse simple set relations, construct and inspect a truth table, and discuss how to identify appropriate raw consistency thresholds.

Day four
We begin with another lab session, rather than a lecture, in which we perform the full analyses of necessity and sufficiency (conservative solution). The rest of the day is dedicated to the presentation and interpretation of the results, feeding back into the notion of QCA as an approach. In the lecture, we will discuss the interpretation of parameters of fit and how to make sense of complex QCA results, using empirical, conceptual, and theoretical knowledge. We will look at different possibilities of presenting QCA results, corresponding good practices and transparency requirements.

Day five
Dedicated to potential pitfalls in QCA in the face of 'noisy' empirical data. Specifically, we will talk about limited diversity, its implications for making counterfactual arguments in comparative research, and possibilities for doing so in QCA when resorting to conservative, intermediate, and parsimonious solution types. We learn the distinction between 'easy' and 'difficult' counterfactuals and their implementation via the so-called 'Standard Analysis'. We touch briefly on the question of what it means for QCA results to be 'robust'. In the lab session, we implement Standard Analysis with R and very briefly look at the issue of model ambiguity. In the remaining time we will discuss some arguments surrounding the debate between QCA 'realists' and 'idealists'.

Before signing up for this course, you must have taken my short course WA102 Foundations of set-theoretic and case-oriented thinking and methodology.

If you can provide evidence of equivalent prior training, you may be admitted to this course, under exceptional circumstances.

Day	Topic	Details
Day 1	QCA: underpinnings, variants, and approaches	Lecture (lecture room, 90’) Origin, dissemination, uses and variants of QCA Calibrating sets QCA as an approach Lab session (computer lab, 90’) Introduction to R using the shiny GUI app Refresher: set relations, INUS and SUIN conditions, Boolean algebra Daily assignment: exercises in Boolean algebra
Day 2	Understanding the technique	Lecture (lecture room, 90’) Calculating membership in sets Parameters of fit Analyzing XY plots Lab session (computer lab, 90’) Set calibration Combining sets Graphs (XY plots and Venn diagrams) Daily assignment: set calibration
Day 3	Let’s do QCA!	Lecture (lecture room, 90’) Analyses of necessity and sufficiency explained: an example A brief treatment of skewed data in QCA Lab session (computer lab, 90’) Manual exercises: Crisp-set QCA Attributing cases to truth table rows With R: Necessity and sufficiency of single conditions Constructing and inspecting a truth table Daily assignment: finding a raw consistency threshold
Day 4	Making sense of QCA	Lab session (computer lab, 90’) Fuzzy-set QCA of necessity and sufficiency (conservative solution) Interpretation of results Daily assignment: simple analysis of necessity and sufficiency with R Lecture (lecture room, 90’) Interpreting parameters of fit and QCA solutions Causal complexity in QCA results Post-QCA case selection Presentation of results and standards of transparency
Day 5	Limited empirical diversity and other potential pitfalls	Lecture (lecture room, 90’) Limited diversity and counterfactual reasoning Conservative, parsimonious and intermediate solution types The Standard Analysis The “problem” of robustness Lab session (computer lab, 90’) Standard Analysis Model ambiguities Discussion: QCA realists and idealists Daily assignment: comparison and discussion of different QCA models

Day	Readings
Day 1	Key readings Berg-Schlosser, D., De Meur, G., Rihoux, B. and C. C. Ragin (2009) Qualitative Comparative Analysis (QCA) as an Approach In Rihoux, B. and C.C. Ragin. Configurational Comparative Methods. Qualitative Comparative Analysis (QCA) and Related Techniques. Los Angeles, London, New Delhi and Singapore: Sage Publications, 1–18 Thomann, E. Qualitative Comparative Analysis (QCA) as a tool for street-level bureaucracy research In: Research Handbook on Street-Level Bureaucracy: The Ground Floor of Government in Context. Edward Elgar, Public Policy Series (Editor Peter Hupe) Ragin, C. C. (2008) Measurement versus calibration: a set-theoretic approach In Box-Steffensmeier, J. M., Brady, H.E. and D. Collier. The Oxford Handbook of Political Methodology. Oxford Handbooks Online: 174–198 Further, optional readings Berg-Schlosser, D. and G. De Meur (2009) Comparative research design: case and variable selection In B. Rihoux and C.C. Ragin (Eds). Configurational Comparative Methods. Qualitative Comparative Analysis (QCA) and Related Techniques (pp. 19–32). Thousand Oaks and London Haesebrouck, T. (2015) The added value of multi-value Qualitative Comparative Analysis Forum Qualitative Sozialforschung/Forum: Qualitative Social Research 17(1) Rihoux, B., Alamos, P., Bol, D., Marx, A. and I. Rezsohazy (2013) From niche to mainstream method? A comprehensive mapping of QCA applications in journal articles from 1984 to 2011 Political Research Quarterly 66(1): 175–184. Schneider, C.Q. and C. Wagemann (2012) Set-Theoretic Methods for the Social Sciences: A Guide to Qualitative Comparative Analysis New York: Cambridge University Press, pp. 23–41 (calibration), 253–274 (variants of QCA) Thiem, A. (2014) Unifying configurational comparative methods: Generalized-set qualitative comparative analysis Sociological Methods & Research 43(2): 313–337. Thomann, E. Oana, E. and S. Wittwer (2018) Performing fuzzy- and crisp set QCA with R: A user-oriented beginner’s guide Chapters 1–3
Day 2	Key readings Rihoux, B. and G. De Meur (2009) Crisp-Set Qualitative Comparative Analysis (csQCA) In Rihoux, B. and C.C. Ragin. Configurational Comparative Methods. Qualitative Comparative Analysis (QCA) and Related Techniques. Los Angeles, London, New Delhi and Singapore: Sage Publications, 33–68 Ragin, C.C. (2009) Qualitative Comparative Analysis Using Fuzzy Sets (fsQCA) In Rihoux, B. and C.C. Ragin. Configurational Comparative Methods. Qualitative Comparative Analysis (QCA) and Related Techniques. Los Angeles, London, New Delhi and Singapore: Sage Publications, 87–121 Schneider, C.Q. and C. Wagemann (2012) Set-Theoretic Methods for the Social Sciences. A Guide to Qualitative Comparative Analysis New York: Cambridge University Press, pp. 117–150 (parameters of fit) Further, optional readings De Block, D. and B. Vis (2018) Addressing the Challenges Related to Transforming Qualitative Into Quantitative Data in Qualitative Comparative Analysis Journal of Mixed Methods Research, doi:1558689818770061 Ragin, C.C. (2006) Set Relations in Social Research: Evaluating Their Consistency and Coverage Political Analysis 14(3): 291–310 Schneider, C.Q. and C. Wagemann (2012) Set-Theoretic Methods for the Social Sciences. A Guide to Qualitative Comparative Analysis New York: Cambridge University Press, pp. 42–90 (Boolean logic and set relations) Thomann, E. Oana, E. and S. Wittwer (2018) Performing fuzzy- and crisp set QCA with R: A user-oriented beginner’s guide Chapters 4–5 Toth, Z., Henneberg, S.C. and P. Naude (2017) Addressing the ‘Qualitative’in fuzzy set Qualitative Comparative Analysis: the generic membership evaluation template Industrial Marketing Management 63: 192–204
Day 3	Key readings Hinterleitner, M., Sager, F. und E. Thomann (2016) The Politics of External Approval: Explaining the IMF’s Evaluation of Austerity Programs European Journal of Political Research 55(3): 549–567 Schneider, C.Q. and C. Wagemann (2012) Set-Theoretic Methods for the Social Sciences. A Guide to Qualitative Comparative Analysis New York: Cambridge University Press, pp. 69–76, 221–232 (necessity), 91–116 (truth tables), 178–194 (truth table algorithm) Further, optional readings Gerrits, L. M. and S. Verweij (2013) Critical Realism as a Meta-Framework for Understanding the Relationships between Complexity and Qualitative Comparative Analysis Journal of Critical Realism 12(2): 166–82 Goertz, G., & Mahoney, J. (2005) Two-level theories and fuzzy-set analysis Sociological Methods & Research, 33(4), 497–538 Goertz, G., & Starr, H. (Eds.). (2002) Necessary conditions: Theory, methodology, and applications Rowman & Littlefield, pp.1–24, 47–94. Oana, I.-E. and C.Q. Schneider. 2018 SetMethods: An Add-on R Package for Advanced QCA The R Journal: 1–27 Ragin, C.C. (1987/2014) The comparative method: Moving beyond qualitative and quantitative strategies University of California Press, pp.85–124 Schneider, C.Q. and C. Wagemann (2012) Set-Theoretic Methods for the Social Sciences. A Guide to Qualitative Comparative Analysis New York: Cambridge University Press, pp. 232–250 (skewed data). Thomann, E. Oana, E. and S. Wittwer (2018) Performing fuzzy- and crisp set QCA with R: A user-oriented beginner’s guide Chapters 6–7.2.
Day 4	Key readings Rihoux, B. and B. Lobe (2009) The case for qualitative comparative analysis (QCA): Adding leverage for thick cross-case comparison The Sage Handbook of Case-Based Methods, pp. 222–242 Schneider, C.Q. and C. Wagemann (2010) Standards of Good Practice in Qualitative Comparative Analysis (QCA) and Fuzzy Sets Comparative Sociology 9(3): 397–418 Wagemann, C. and C.Q. Schneider (2015) Transparency Standards in Qualitative Comparative Analysis Qualitative and Multi-Method Research: Newsletter of the American Political Science Association’s QMMR Section 13(1): 38–42 Further, optional readings Castro, R. G. and M.A. Ariño (2016) A general approach to panel data set-theoretic research Journal of Advances in Management Sciences & Information Systems 2: 63–76 Fischer, M., & Maggetti, M. (2017) Qualitative comparative analysis and the study of policy processes Journal of Comparative Policy Analysis: Research and Practice, 19(4), 345–361 Thiem, A., Baumgartner, M. and D. Bol (2016) Still Lost in Translation! A Correction of Three Misunderstandings between Configurational Comparativists and Regressional Analysts Comparative Political Studies, 49(6) 742–774 Thomann, E. Oana, E. and S. Wittwer (2018) Performing fuzzy- and crisp set QCA with R: A user-oriented beginner’s guide Chapter 8 Ragin, C.C. (1987/2014) The comparative method: Moving beyond qualitative and quantitative strategies University of California Press, pp. 164–172 Schneider, C. Q, and I. Rohlfing (2013) Combining QCA and process tracing in set-theoretic multi-method research Sociological Methods & Research 42(4): 559–597 Williams, T. and S.M. Gemperle (2017) Sequence will tell! Integrating temporality into set-theoretic multi-method research combining comparative process tracing and qualitative comparative analysis International Journal of Social Research Methodology 20(2): 121–135
Day 5	Key readings Schneider, C.Q. and C. Wagemann (2012) Set-Theoretic Methods for the Social Sciences: A Guide to Qualitative Comparative Analysis New York: Cambridge University Press, pp. 15–177 (limited diversity and Standard Analysis), 284–294 (robustness) Thomann, E. and M. Maggetti (2017) Designing Research with Qualitative Comparative Analysis (QCA): Approaches, Challenges, and Tools Sociological Methods & Research, DOI: 10.1177/0049124117729700. Further, optional readings Baumgartner, M. (2015) Parsimony and Causality Quality & Quantity 49: 83–856 Baumgartner, M. and A. Thiem (2017) Model ambiguities in configurational comparative research Sociological Methods & Research 46(4): 954–987 Emmenegger, P. (2011) How good are your counterfactuals? Assessing quantitative macro-comparative welfare state research with qualitative criteria Journal of European Social Policy 21(4): 365–380 Maggetti, M. and D. Levi-Faur (2013) Dealing with Errors in QCA Political Research Quarterly 66(1): 198–204 Radaelli, C.M. and C. Wagemann (2018) What did I leave out? Omitted variables in regression and qualitative comparative analysis European Political Science, DOI: 10.1057/s41304-017-0142-7 Ragin, C.C. (2008) Easy Versus Difficult Counterfactuals Redesigning Social Inquiry: Set Relations in Social Research. Chicago: University of Chicago Press, chapter 9 Rohlfing, I. (2018) Power and False Negatives in Qualitative Comparative Analysis: Foundations, Simulation and Estimation for Empirical Studies Political Analysis 26(1): 72–89 Schneider, C.Q. (2018) Realists and Idealists in QCA Political Analysis, DOI: 10.1017/pan.2017. 45 Schneider, C.Q. and C. Wagemann (2013) Doing Justice to Logical Remainders in QCA: Moving Beyond the Standard Analysis Political Research Quarterly 66(1): 211–220 Skaaning, S. (2011) Assessing the robustness of crisp-set and fuzzy-set QCA results Sociological Methods & Research 40(2): 391–408 Thomann, E. Oana, E. and S. Wittwer (2018) Performing fuzzy- and crisp set QCA with R: A user-oriented beginner’s guide Chapters 7.3–7.5

Software Requirements

R and Rstudio (freeware; latest versions)
Web browser: Google chrome as standard browser

Hardware Requirements

You can bring your own laptop – Mac and PC are ok. Please instal Google Chrome as your standard web browser before the first session.

Computers will be provided for the lab sessions.

Literature

Duşa, A. (2018)
QCA with R: A Comprehensive Resource
New York: Springer International Publishing

Ragin, C. C. (2000)
Fuzzy-set social science
Chicago and London: University of Chicago Press

Ragin, C. C. (2009)
Redesigning social inquiry: Fuzzy sets and beyond
Chicago: University of Chicago Press

Rihoux, B. and C.C. Ragin
Configurational Comparative Methods. Qualitative Comparative Analysis (QCA) and Related Techniques
Los Angeles, London, New Delhi and Singapore: Sage Publications

Schneider, C.Q. and C. Wagemann (2012)
Set-Theoretic Methods for the Social Sciences. A Guide to Qualitative Comparative Analysis
New York: Cambridge University Press

Thomann, E. (2018)
Customized implementation of European Union food safety policy: United in diversity?
Palgrave Macmillan, International Series on Public Policy

Thomann, E. Oana, E. and S. Wittwer (2018)
Performing fuzzy- and crisp set QCA with R: A user-oriented beginner’s guide

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Summer School

R Basics
Multi-Method Research: Techniques and Applications
Case Study Research: Method and Practice
Qualitative Data Analysis: Concepts and Approaches
Knowing and the Known: The Philosophy and Methodology of the Social Sciences
Seasoned Scholars Workshop: Multi-Method Designs, Case-Oriented and Comparative Methods

Winter School

Foundations of Set-Theoretic and Case-Oriented Thinking and Methodology (required)
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