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Set Relations in Social Research: Evaluating Their Consistency and Coverage

Published online by Cambridge University Press:  04 January 2017

Charles C. Ragin
Charles C. Ragin*
Affiliation:
Department of Sociology, University of Arizona, Tucson, AZ 85721. e-mail: cragin@email.arizona.edu
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Abstract

Because of its inherently asymmetric nature, set-theoretic analysis offers many interesting contrasts with analysis based on correlations. Until recently, however, social scientists have been slow to embrace set-theoretic approaches. The perception was that this type of analysis is restricted to primitive, binary variables and that it has little or no tolerance for error. With the advent of “fuzzy” sets and the recognition that even rough set-theoretic relations are relevant to theory, these old barriers have crumbled. This paper advances the set-theoretic approach by presenting simple descriptive measures that can be used to evaluate set-theoretic relationships, especially relations between fuzzy sets. The first measure, “consistency,” assesses the degree to which a subset relation has been approximated, whereas the second measure, “coverage,” assesses the empirical relevance of a consistent subset. This paper demonstrates further that set-theoretic coverage can be partitioned in a manner somewhat analogous to the partitioning of explained variation in multiple regression analysis.

Information

Type
Research Article
Information
Political Analysis , Volume 14 , Issue 3: Special Issue on Causal Complexity and Qualitative Methods , Summer 2006, pp. 291 - 310
Copyright
Copyright © The Author 2006. Published by Oxford University Press on behalf of the Society for Political Methodology 

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References

Braumoeller, Bear, and Goertz, Gary. 2000. The methodology of necessary conditions. American Journal of Political Science 44(4): 844–58.CrossRefGoogle Scholar
De Meur, Gisèie, and Rihoux, Benoît. 2002. L'Analyse Quali-Quantitative Comparée: Approche, Techniques et applications en sciences humaines. Louvain-la-Neuve: Bruylant-Academia.Google Scholar
Dion, Douglas. 1998. Evidence and inference in the comparative case study. Comparative Politics 30(2): 127–45.CrossRefGoogle Scholar
George, Alexander. 1979. Case studies and theory development: The method of structured, focussed comparison. In Diplomacy: New approaches in history, theory and policy, ed. Lauren, Paul G., 43–68. New York: Free Press.Google Scholar
George, Alexander, and Bennett, Andrew. 2005. Case studies and theory development. Cambridge: MIT Press.Google Scholar
Goertz, Gary. 2002. The substantive importance of necessary conditions hypotheses. In Necessary conditions: Theory, methodology, and applications, ed. Goertz, Gary and Starr, Harvey, 65–94. New York: Rowman & Littlefield.Google Scholar
Goertz, Gary. 2003. Assessing the importance of necessary or sufficient conditions in fuzzy-set social science. Compasss Working Paper WP2003-7. www.compasss.org/wp.htm.Google Scholar
Goertz, Gary. 2005. Social Science Concepts: A User's Guide. Princeton: Princeton University Press.Google Scholar
Goertz, Gary. 2006. Assessing the trivialness, relevance, and relative importance of necessary or sufficient conditions in social science. Studies in Comparative International Development. Forthcoming.CrossRefGoogle Scholar
Goertz, Gary, and Starr, Harvey, eds. 2002. Necessary conditions: Theory, methodology, and applications. New York: Rowman & Littlefield.Google Scholar
Herrnstein, Richard, and Murray, Charles. 1994. The bell curve: Intelligence and class structure in American life. New York: Free Press.Google Scholar
Kosko, Bart. 1993. Fuzzy thinking: The new science of fuzzy logic. New York: Hyperion.Google Scholar
Lieberson, Stanley. 1985. Making it count: The improvement of social research and theory. Berkeley: University of California Press.Google Scholar
Lieberson, Stanley. 2004. Comments on the use and utility of QCA. Qualitative Methods. Newsletter of the America Political Science Association Organized Section on Qualitative Methods 2(2): 13–4.Google Scholar
Mackie, John L. 1965. Causes and conditionals. American Philosophical Quarterly 2: 245–65.Google Scholar
Peceny, Mark, and Beer, Caroline C. 2002. Dictatorial peace? American Political Science Review 96: 15–26.Google Scholar
Ragin, Charles C. 1987. The comparative method: Moving beyond qualitative and quantitative strategies. Berkeley: University of California Press.Google Scholar
Ragin, Charles C. 2000. Fuննy-set social science. Chicago: University of Chicago Press.Google Scholar
Ragin, Charles C. 2003. Recent advanced in fuzzy-set methods and their application to policy questions. Compasss Working Paper WP2003-9. www/compasss.org/wp.htm.Google Scholar
Ragin, Charles C. 2004. From fuzzy sets to crisp truth tables. Compasss Working Paper WP2004-28. www.compasss.org/wp.htm.Google Scholar
Ragin, Charles C. 2006. The Limitations of net effects thinking. In Innovative comparative methods for policy analysis, ed. Grimm, Heike and Rihoux, Benoit, 13–41. Springer.CrossRefGoogle Scholar
Ragin, Charles C., Drass, Kriss A., and Davey, Sean. 2003. Fuzzy-set/qualitative comparative analysis, version 2.0. www.u.arizona.edu/∼cragin/fsQCA/download/Setup_fsQCA.exe.Google Scholar
Ragin, Charles C., and Giesel, H. 2003. User's guide to fuzzy-set/qualitative comparative analysis. www.u.arizona.edu/∼cragin/fsQCA/download/fsQCAManual.pdf.Google Scholar
Ragin, Charles C., and Rihoux, Benoît. 2004. Qualitative comparative analysis (QCA): State of the art and prospects. Qualitative Methods. Newsletter of the America Political Science Association Organized Section on Qualitative Methods 2(2): 3–13.Google Scholar
Rihoux, Benoît. 2003. Bridging the gap between the qualitative and quantitative worlds? A retrospective and prospective view on qualitative comparative analysis. Field Methods 15(4): 351–65.CrossRefGoogle Scholar
Smithson, Michael, and Verkuilen, Jay. 2006. Fuzzy set theory. Thousand Oaks, CA: Sage.CrossRefGoogle Scholar