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WB105 - Introduction to Qualitative Comparative Analysis (QCA)

Instructor Details

Instructor Photo

Eva Thomann

Institution:
University of Exeter

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

Eva Thomann @EvaThomann


Course Dates and Times

Monday 17 – Friday 21 February, 09:00–12:30
15 hours over five days

Prerequisite Knowledge

Before signing up for this course, you should have taken Eva's short course Foundations of set-theoretic and case-oriented methods.

If you can provide evidence of equivalent prior training, you may be admitted to this course. In case of doubt, please contact the instructor via email.

‘The dense theoretical part of this course grasps the very foundations of QCA and clarifies doubts on your research design. The practical element in the lab is also helpful for those, like me, who are beginners in R. Eva Thomann and her assistants were well-prepared, eager to help, and entertaining. I highly recommend this course!’ ꟷ Adriana Cuppuleri, School of International Studies, University of Trento

Attended this course in 2019
Short Outline

This course introduces you to crisp set and fuzzy set Qualitative Comparative Analysis (QCA) and its analysis in R. 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 (2,500–4,000 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 6 March 2020.

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.

Long Course Outline

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 and scripts. 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 using either code or the user-friendly 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, which has an introductory and applied character, presupposes the knowledge and skills taught in the short course Foundations of set-theoretic and case-oriented methods.

It will not cover advanced analytic tools for QCA 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 2020 Summer School in Budapest and the Advanced Topics in Set-Theoretic Methods and QCA course at our 2021 Winter Methods School.

We will use the R packages QCA (and where warranted, SetMethods) and work primarily with command lines offering the most advanced functionality for QCA software. If you are not interested in working with code, we will also introduce the user-friendly, interactive graphical interface (shiny GUI app) offering more basic functionality. We will document our work in R scripts and discuss how to interpret and work with R commands. The course will give you basic familiarity with R and enable you to transparently document your analysis for replication. You will need further training or self-study to gain full proficiency in R.

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 RStuddio and 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 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 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 solutions types. We will learn about the distinction between 'easy' and 'difficult' counterfactuals and their implementation via the so-called 'Standard Analysis'. In the lab session, we implement Standard Analysis with R and very briefly look at the issue of model ambiguity. 

Day-to-Day Schedule

Day-to-Day Reading List

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 install 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

Mello, P.A.  (forthcoming)
Qualitative Comparative Analysis: Research Design and Application
Washington DC: Georgetown University Press

Oana, I.E., Schneider, C.Q. and E. Thomann (forthcoming)
Qualitative Comparative Analysis (QCA) using R
Cambridge: Cambridge University Press

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

The following other ECPR Methods School courses could be useful in combination with this one in a ‘training track .
Recommended Courses Before

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 Methods (required)
Introduction to R (entry level)
Working with Concepts in the Social Sciences
Comparative Research Design

Recommended Courses After

Summer School

Process Tracing Methodology I and II
Qualitative Comparative Analysis and Fuzzy Sets (week 2)
Intermediate R: Capacities for Analysis and Visualisation

Winter School

Process Tracing Methods
Advanced Topics in Set-Theoretic Methods and QCA
Analysing Political and Social Sequences

Additional Information

Disclaimer

This course description may be subject to subsequent adaptations (e.g. taking into account new developments in the field, participant demands, group size, etc). Registered participants will be informed in due time.

Note from the Academic Convenors

By registering for this course, you confirm that you possess the knowledge required to follow it. The instructor will not teach these prerequisite items. If in doubt, contact the instructor before registering.


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