Qualitative Comparative Analysis

Set-Theoretic Methods: QCA and Fuzzy Sets

 

Prerequirements

Participants are not required to have any prior knowledge of QCA or the R software environment and the package relevant for set-theoretic methods. However, they would profit from prior empirical-comparative training. Participants should read the basic readings listed below before the course starts. An introduction to the basic functions of R and RStudio will be provided on day 1, but if participants try out these software packages in advance, they will find it easier to follow.

 

Course content

This course introduces participants to set-theoretic methods and their application in the social sciences with a focus on Qualitative Comparative Analysis. The course starts out by familiarizing students with the basic concepts of the underlying methodological perspective, among them the central notions of necessity and sufficiency, formal logic and Boolean algebra. From there, we move to the logic and analysis of truth tables and discuss the most important problems that emerge when this analytical tool is used for exploring social science data. Right from the beginning, students will be exposed to performing set-theoretic analyses with the relevant R software packages. When discussing set-theoretic methods, in-class debates will engage on broad, general comparative social research issues, such as case selection principles, concept formation, questions of data aggregation and the treatment of causally relevant notions of time. Examples are drawn from published applications in the social sciences. Participants are encouraged to bring their own raw data for in-class exercises and assignments, if available. By the end of the course, participants will be able to perform set-theoretic analyses of their own and to critically evaluate published QCA.

 

Structure

The central aim of the first half of the course is to familiarize the participants with the formal logic of set-theoretic methods and to introduce QCA as an approach, its main assumptions, the technical environment (software) and the standard procedures and operations. Particular emphasis is put on a thorough understanding of the notions of necessity and sufficiency, as they are the nuts and bolts of QCA that set it apart from the majority of other available cross-case comparative techniques.

The purpose of the second half of the course is fourfold: (1) to re-visit the core features of QCA addressed so far (calibration, tests of necessity and sufficiency, truth tables, parameters of fit); (2) to elaborate on further issues that arise when neat formal logical tools and concepts are applied to social science data (mainly the issues of limited diversity and the challenge to make good counterfactuals on so-called logical remainders); (3) to get better acquainted with the standards of good practice, both in its fundamental aspects and in using the relevant software programmes; (4) to discuss general methodological issues, such as robustness and theory evaluation from a set-theoretic point of view.

Throughout the course, we will analyse fake and real data in the computer lab, using the R software environment and its QCA package. In addition to prepared datasets, which will be made available, participants are encouraged to bring their own raw data (even if this data is still tentative), which can be used for lab exercises and project work.

 

Literature

  

Recommended readings (*compulsory text)
Day 1

*Schneider, Carsten Q. and Claudius Wagemann (2012). Set-Theoretic Methods for the Social Sciences: A Guide to Qualitative Comparative Analysis. Cambridge: Cambridge University Press, pp. 1-20.

*Schneider, Carsten Q. and Claudius Wagemann (2012). Set-Theoretic Methods for the Social Sciences: A Guide to Qualitative Comparative Analysis. Cambridge: Cambridge University Press, pp. 21-31; 42-90.

Goertz, Gary and James Mahoney (2012). A Tale of Two Cultures: Qualitative and Quantitative Research in the Social Sciences. Princeton: Princeton University Press, chapter 2.

Ragin, Charles C. (1987). The Comparative Method. Moving Beyond Qualitative and Quantitative Strategies. Berkeley: University of California Press, chapter 6.

Day 2

*Schneider, Carsten Q. and Claudius Wagemann (2012). Set-Theoretic Methods for the Social Sciences: A Guide to Qualitative Comparative Analysis. Cambridge: Cambridge University Press, pp. 32-41, 76-90.

Ragin, Charles C. (2008). Redesigning Social Inquiry: Fuzzy Sets and Beyond. Chicago: University of Chicago Press, chapters 4 & 5.

Rohlfing, Ingo (2012). Case Studies and Causal Inference: An Integrative Framework. Basingstoke: Palgrave Macmillan, chapter 2.

*Schneider, Carsten Q. and Claudius Wagemann (2012). Set-Theoretic Methods for the Social Sciences: A Guide to Qualitative Comparative Analysis. Cambridge: Cambridge University Press, pp. 91-115.

Ragin, Charles C. (2008). Redesigning Social Inquiry: Fuzzy Sets and Beyond. Chicago: University of Chicago Press chapter 7.

Day 3

*Schneider, Carsten Q. and Claudius Wagemann (2012). Set-Theoretic Methods for the Social Sciences: A Guide to Qualitative Comparative Analysis. Cambridge: Cambridge University Press, pp. 119-150.

Ragin, Charles C. (2008). Redesigning Social Inquiry: Fuzzy Sets and Beyond. Chicago: University of Chicago Press, chapter 3.

*Schneider, Carsten Q. and Claudius Wagemann (2012). Set-Theoretic Methods for the Social Sciences: A Guide to Qualitative Comparative Analysis. Cambridge: Cambridge University Press, chapter 9.2.

Goertz, Gary (2006). “Assessing the Trivialness, Relevance, and Relative Importance of Necessary or Sufficient Conditions in Social Science.” Studies in Comparative International Development 41(2): 88-109.

*Schneider, Carsten Q. and Claudius Wagemann (2012). Set-Theoretic Methods for the Social Sciences: A Guide to Qualitative Comparative Analysis. Cambridge: Cambridge University Press, chapter 7

Ragin, Charles C. (2008). Redesigning Social Inquiry: Fuzzy Sets and Beyond. Chicago: University of Chicago Press, chapter 9.

Day 4

*Schneider, Carsten Q. and Claudius Wagemann (2012). Set-Theoretic Methods for the Social Sciences: A Guide to Qualitative Comparative Analysis. Cambridge: Cambridge University Press, chapter 6.

Ragin, Charles C. (1987). The Comparative Method. Moving Beyond Qualitative and Quantitative Strategies. Berkeley: University of California Press, chapter 7.

Ragin, Charles C. (2008). Redesigning Social Inquiry: Fuzzy Sets and Beyond. Chicago: University of Chicago Press, chapters 8 & 9.

*Schneider, Carsten Q. and Claudius Wagemann (2012). Set-Theoretic Methods for the Social Sciences: A Guide to Qualitative Comparative Analysis. Cambridge: Cambridge University Press, chapter 8.

Emmenegger, Patrick (2012). “How Good Are Your Counterfactuals? Assessing Quantitative Macro-Comparative Welfare State Research.” Journal of European Social Policy, 21 (4): 365-80.

Day 5

*Schneider, Carsten Q. and Ingo Rohlfing (2013). “Set-Theoretic Methods and Process Tracing in Multi-Method Research: Principles of Case Selection after QCA.” Sociological Methods and Research, DOI: 10.1177/0049124113481341

*Schneider, Carsten Q. and Claudius Wagemann (2012). Set-Theoretic Methods for the Social Sciences: A Guide to Qualitative Comparative Analysis. Cambridge: Cambridge University Press, chapters 11.1 and conclusion.

Rohlfing, Ingo and Carsten Q. Schneider (2013) “Combining QCA With Process Tracing in Analyses of Necessity.” Political Research Quarterly 66(1): 220–35.

 

Exam

The course grade consists of 20% in-class participation and 80% final paper.

For the final paper, participants receive a published article that uses QCA and the data based on which the QCA is performed in this article. The task is to very briefly summarize the findings of the article (max. 1/10); to replicate these findings (max. 4/10); and to perform additional meaningful analyses on the data (1/2).

In addition to the paper, participants must submit a clean R code, whereby clean means that the script is running without errors, has succinct but informative lines commenting the commands that follow, and that produces all the analytic results that are used in the paper. In short, it should be a real replication file.

The final paper should be like a real paper, with formatted text, coherent sentences, meaningful tables and figures with numbered headings, a reference list, and an appendix.

The paper should be not longer than 15 pages, 12 points font size, and 1.5 line space.

The paper needs to be submitted within 14 days after the course has finished. It is an open book task.

 

In order to successfully pass the final paper task, participants must make use of the knowledge acquired during the course. This includes issues such as set calibration, creation of a truth table, parameters of fit, skewed sets, treatment of logical remainders, (enhanced) standard analyses, set-theoretic multi-method research, theory evaluation, and temporal QCA.

 

All of the above-listed mandatory readings are required for the final paper.