Hostname: page-component-76fb5796d-2lccl Total loading time: 0 Render date: 2024-04-26T07:04:50.429Z Has data issue: false hasContentIssue false

Enhancing Sensitivity Diagnostics for Qualitative Comparative Analysis: A Combinatorial Approach

Published online by Cambridge University Press:  04 January 2017

Alrik Thiem*
Affiliation:
Department of Philosophy, University of Geneva, Rue de Candolle 2/Bât. Landolt, 1211 Geneva, Switzerland
Reto Spöhel
Affiliation:
Department of Engineering and Information Technology, Bern University of Applied Sciences, Pestalozzistrasse 20, 3400 Burgdorf, Switzerland, e-mail: reto.spoehel@bfh.ch
Adrian Duşa
Affiliation:
Department of Sociology, University of Bucharest, Soseaua Panduri 90, 050663 Bucharest, Romania, e-mail: dusa.adrian@unibuc.ro
*
e-mail: alrik.thiem@unige.ch (corresponding author)

Abstract

Sensitivity diagnostics has recently been put high on the agenda of methodological research into Qualitative Comparative Analysis (QCA). Existing studies in this area rely on the technique of exhaustive enumeration, and the majority of works examine the reactivity of QCA either only to alterations in discretionary parameter values or only to data quality. In this article, we introduce the technique of combinatorial computation for evaluating the interaction effects between two problems afflicting data quality and two discretionary parameters on the stability of QCA reference solutions. In this connection, we challenge a hitherto unstated assumption intrinsic to exhaustive enumeration, show that combinatorial computation permits the formulation of general laws of sensitivity in QCA, and demonstrate that our technique is most efficient.

Type
Articles
Copyright
Copyright © The Author 2015. Published by Oxford University Press on behalf of the Society for Political Methodology 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Authors' note: Supplementary materials for this article are available on the Political Analysis Web site (Thiem, Spöhel, and Dus'a 2015). Previous versions of this article have been presented at the 1st and 2nd International QCA Expert Workshops, ETH Zurich, Switzerland. We thank Michael Baumgartner, Christian Rupietta, the participants at the aforementioned workshops, the editors of Political Analysis, and the three reviewers for their helpful comments.

References

Ambuehl, Mathias, Baumgartner, Michael, Epple, Ruedi, Kauffmann, Alexis, and Thiem, Alrik. 2015. cna: A package for Coincidence Analysis, R package version 1.0-3. http://cran.r-project.org/package=cna.Google Scholar
Baumgartner, Michael. 2009. Inferring causal complexity. Sociological Methods & Research 38(1): 71101.CrossRefGoogle Scholar
Baumgartner, Michael. 2013. Detecting causal chains in small-n data. Field Methods 25(1): 324.CrossRefGoogle Scholar
Baumgartner, Michael. 2015. Parsimony and causality. Quality & Quantity 49(2): 839–56.CrossRefGoogle Scholar
Baumgartner, Michael, and Thiem, Alrik. 2015a. Identifying complex causal dependencies in configurational data with Coincidence Analysis. The R Journal 7(1): 176–84.CrossRefGoogle Scholar
Baumgartner, Michael, and Thiem, Alrik. 2015b. Model ambiguities in configurational comparative research. Sociological Methods & Research. Advance online publication. DOI: 10.1177/0049124115610351.CrossRefGoogle Scholar
Baumgartner, Michael, and Epple, Ruedi. 2014. A Coincidence Analysis of a causal chain: The Swiss minaret vote. Sociological Methods & Research 43(2): 280312.CrossRefGoogle Scholar
Bol, Damien, and Luppi, Francesca. 2013. Confronting theories based on necessary relations: Making the best of QCA possibilities. Political Research Quarterly 66(1): 205–10.Google Scholar
Bowers, Jake. 2014. Comment: Method games—A proposal for assessing and learning about methods. Sociological Methodology 44(1): 112–7.CrossRefGoogle Scholar
Braumoeller, Bear F. 2015. Guarding against false positives in Qualitative Comparative Analysis. Political Analysis. Advance online publication. DOI: 10.1093/pan/mpv017.CrossRefGoogle Scholar
Braumoeller, Bear F., and Goertz, Gary. 2000. The methodology of necessary conditions. American Journal of Political Science 44(4): 844–58.CrossRefGoogle Scholar
Clark, William Roberts, Gilligan, Michael J., and Golder, Matt. 2006. A simple multivariate test for asymmetric hypotheses. Political Analysis 14(3): 311–31.CrossRefGoogle Scholar
Cooper, Barry, and Glaesser, Judith. 2011a. Paradoxes and pitfalls in using fuzzy set QCA: Illustrations from a critical review of a study of educational inequality. Sociological Research Online 16(3): 18.CrossRefGoogle Scholar
Cooper, Barry, and Glaesser, Judith. 2011b. Using case-based approaches to analyse large datasets: A comparison of Ragin's fsQCA and fuzzy cluster analysis. International Journal of Social Research Methodology 14(1): 3148.CrossRefGoogle Scholar
Coverdill, James E., and Finlay, William. 1995. Understanding mills via Mill-type methods: An application of Qualitative Comparative Analysis to a study of labor management in Southern textile manufacturing. Qualitative Sociology 18(4): 457–78.CrossRefGoogle Scholar
Cronqvist, Lasse, and Berg-Schlosser, Dirk. 2009. Multi-value QCA (mvQCA). In Configurational comparative methods: Qualitative Comparative Analysis (QCA) and related techniques, eds. Rihoux, Benoît and Ragin, Charles C., 6986. London: Sage Publications.CrossRefGoogle Scholar
Duşa, Adrian, and Thiem, Alrik. 2014. QCA: A package for Qualitative Comparative Analysis, R package version 1.1-4. http://cran.r-project.org/package =QCA.Google Scholar
Duşa, Adrian, and Thiem, Alrik. 2015. Enhancing the minimization of Boolean and multi-value output functions with eQMC. Journal of Mathematical Sociology 39(2): 92108.CrossRefGoogle Scholar
Eliason, Scott R., and Stryker, Robin. 2009. Goodness-of-fit tests and descriptive measures in fuzzy-set analysis. Sociological Methods & Research 38(1): 102–46.CrossRefGoogle Scholar
Gelman, Andrew, and Hill, Jennifer. 2007. Data analysis using regression and multilevel/hierarchical models. Cambridge, UK: Cambridge University Press.Google Scholar
Glaesser, Judith, and Cooper, Barry. 2014. Exploring the consequences of a recalibration of causal conditions when assessing sufficiency with fuzzy set QCA. International Journal of Social Research Methodology 17(4): 387401.CrossRefGoogle Scholar
Goldthorpe, John H. 1997a. Current issues in comparative macrosociology: A debate on methodological issues. Comparative Social Research 16:126.Google Scholar
Goldthorpe, John H 1997b. A response to the commentaries. Comparative Social Research 16:121–32.Google Scholar
Griffin, Larry J., Botsko, Ana-Maria Wahl, Christopher, and Isaac, Larry W. 1991. Theoretical generality, case particularity: Qualitative Comparative Analysis of trade-union growth and decline. International Journal of Comparative Sociology 32(1–2): 110–36.CrossRefGoogle Scholar
Grofman, Bernard, and Schneider, Carsten Q. 2009. An introduction to crisp set QCA, with a comparison to binary logistic regression. Political Research Quarterly 62(4): 662–72.CrossRefGoogle Scholar
Hicks, Alexander, Misra, Joya, and Nah Ng, Tang. 1995. The programmatic emergence of the social security state. American Sociological Review 60(3): 329–49.CrossRefGoogle Scholar
Hohn, Franz E. 1966. Applied Boolean algebra: An elementary introduction. New York: Macmillan.Google Scholar
Hug, Simon. 2013. Qualitative Comparative Analysis: How inductive use and measurement error lead to problematic inference. Political Analysis 21(2): 252–65.CrossRefGoogle Scholar
Krogslund, Chris, Danny Choi, Donghyun, and Poertner, Mathias. 2015. Fuzzy sets on shaky ground: Parameter sensitivity and confirmation bias in fsQCA. Political Analysis 23(1): 2141.CrossRefGoogle Scholar
Lucas, Samuel R., and Szatrowski, Alisa. 2014. Qualitative Comparative Analysis in critical perspective. Sociological Methodology 44(1): 179.CrossRefGoogle Scholar
Maggetti, Martino, and Levi-Faur, David. 2013. Dealing with errors in QCA. Political Research Quarterly 66(1): 198204.Google Scholar
Nievergelt, Jürg. 2000. Exhaustive search, combinatorial optimization and enumeration: Exploring the potential of raw computing power. In SOFSEM 2000: Theory and practice of informatics, eds. Hlaváč, Václav, Jeffery, Keith G., and Wiedermann, Jiří, 1835. Berlin: Springer.CrossRefGoogle Scholar
Paine, Jack. 2015. Set-theoretic comparative methods: Less distinctive than claimed. Comparative Political Studies. Advance online publication. DOI: 10.1177/0010414014564851.CrossRefGoogle Scholar
R Development Core Team. 2014. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.Google Scholar
Ragin, Charles C. 2000. Fuzzy-set social science. Chicago: University of Chicago Press.Google Scholar
Ragin, Charles C., and Davey, Sean. 2014. fs/QCA: Fuzzy-set/Qualitative Comparative Analysis, version 2.5 [computer program]. Irvine: Department of Sociology, University of California.Google Scholar
Sarkar, Deepayan. 2008. Lattice: Multivariate data visualization with R. New York: Springer.CrossRefGoogle Scholar
Schneider, Carsten Q., and Wagemann, Claudius. 2012. Set-theoretic methods for the social sciences: A guide to Qualitative Comparative Analysis (QCA). Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Schneider, Carsten Q., and Wagemann, Claudius 2013. Doing justice to logical remainders in QCA: Moving beyond the standard analysis. Political Research Quarterly 66(1): 211–20.Google Scholar
Seawright, Jason. 2005. Qualitative Comparative Analysis vis-à-vis regression. Studies in Comparative International Development 40(1): 326.CrossRefGoogle Scholar
Seawright, Jason. 2014. Comment: Limited diversity and the unreliability of QCA. Sociological Methodology 44(1): 118–21.CrossRefGoogle Scholar
Skaaning, Svend-Erik. 2011. Assessing the robustness of crisp-set and fuzzy-set QCA results. Sociological Methods & Research 40(2): 391408.CrossRefGoogle Scholar
Thiem, Alrik. 2013. Clearly crisp, and not fuzzy: A reassessment of the (putative) pitfalls of multi-value QCA. Field Methods 25(2): 197207.CrossRefGoogle Scholar
Thiem, Alrik. 2014a. Membership function sensitivity of descriptive statistics in fuzzy-set relations. International Journal of Social Research Methodology 17(6): 625–42.CrossRefGoogle Scholar
Thiem, Alrik. 2014b. Mill's methods, induction and case sensitivity in Qualitative Comparative Analysis: A comment on Hug (2013). Qualitative & Multi-Method Research 12(2): 1924.Google Scholar
Thiem, Alrik 2014c. Navigating the complexities of Qualitative Comparative Analysis: Case numbers, necessity relations, and model ambiguities. Evaluation Review 38(6): 487513.CrossRefGoogle ScholarPubMed
Thiem, Alrik. 2014d. Unifying configurational comparative methods: Generalized-set Qualitative Comparative Analysis. Sociological Methods & Research 43(2): 313–37.CrossRefGoogle Scholar
Thiem, Alrik. 2015. Using Qualitative Comparative Analysis for identifying causal chains in configurational data: A methodological commentary on Baumgartner and Epple (2014). Sociological Methods & Research 44(4): 723–36.CrossRefGoogle Scholar
Thiem, Alrik, and Duşa, Adrian. 2013a. Boolean minimization in social science research: A review of current software for Qualitative Comparative Analysis (QCA). Social Science Computer Review 31(4): 505–21.CrossRefGoogle Scholar
Thiem, Alrik, and Duşa, Adrian. 2013b. QCA: A package for Qualitative Comparative Analysis. The R Journal 5(1): 8797.CrossRefGoogle Scholar
Thiem, Alrik, and Duşa, Adrian 2013c. Qualitative Comparative Analysis with R: A user's guide. New York: Springer.CrossRefGoogle Scholar
Thiem, Alrik, Baumgartner, Michael, and Bol, Damien. 2015. Still lost in translation! A correction of three misunderstandings between configurational comparativists and regressional analysts. Comparative Political Studies. Advance online publication. DOI: 10.1177/0010414014565892.CrossRefGoogle Scholar
Thiem, Alrik, Spöhel, Reto, and Duşa, Adrian. 2015. Replication Package for: Enhancing sensitivity diagnostics for Qualitative Comparative Analysis: A combinatorial approach. http://dx.doi.org/10.7910/DVN/QE27H9, Harvard Dataverse, V1.CrossRefGoogle Scholar
Vis, Barbara. 2012. The comparative advantages of fsQCA and regression analysis for moderately large- n analyses. Sociological Methods & Research 41(1): 168–98.CrossRefGoogle Scholar
Wooldridge, Jeffrey M. 2002. Econometric analysis of cross section and panel data. Cambridge, MA: MIT Press.Google Scholar