Using case-based approaches to analyse large datasets: A comparison of ragin's fsQCA and fuzzy cluster analysis

International Journal of Social Research Methodology

Volumn 14, Issue 1, 2011, Pages 31-48

  Cooper, Barry ^a   Glaesser, Judith ^a  

^a DURHAM UNIVERSITY   (United Kingdom)

Author keywords

Classification of cases; Fs QCA; Fuzzy cluster analysis; National child development study; Social class and education

Indexed keywords

EID: 78650059302     PISSN: 13645579     EISSN: 14645300     Source Type: Journal    
DOI: 10.1080/13645579.2010.483079     Document Type: Article

References (39)

1. Abbott, A. (2001). Time matters. London/Chicago: Chicago University Press.
2. Bailey, K.D. (1994). Typologies and taxonomies. Thousand Oaks, CA: Sage.
3. Boudon, R. (1974). The logic of sociological explanation. Harmondsworth: Penguin.
4. Byrne, D. (2002). Analysing quantitative data. London: Sage.
5. Cheli, B., & Lemmi, A. (1995). A 'totally fuzzy and relative' approach to the measurement of poverty. Economic Notes, 94(1), 115-134.
6. Cooper, B. (2005a). Applying Ragin's crisp and fuzzy set QCA to large datasets: Social class and educational achievement in the National Child Development Study. Sociological Research Online, 10(2).
7. Cooper, B. (2005b). On applying Ragin's crisp and fuzzy set QCA to large datasets. European Consortium for Political Research conference, Budapest. Retrieved September 15, 2009, from, http://www.essex.ac.uk/ecpr/events/generalconference/budapest/papers/20/6/cooper.pdf
8. Cooper, B. (2006, April). Using Ragin's Qualitative Comparative Analysis with longitudinal datasets to explore the degree of meritocracy characterising educational achievement in Britain. Paper presented at the annual meeting of the American Educational Research Association, San Francisco.
9. Cooper, B., & Glaesser, J. (2007, April). Exploring social class compositional effects on educational achievement with fuzzy set methods: A British study. Paper presented at the annual meeting of the American Educational Research Association, Chicago.
10. Cooper, B., & Glaesser, J. (2008). How has educational expansion changed the necessary and sufficient conditions for achieving professional, managerial and technical class positions in Britain? A configurational analysis. Sociological Research Online, 13(3).
11. de Oliveira, J.V., & Pedrycz, W. (Eds.). (2007). Advances in fuzzy clustering and its applications. New York: Wiley.
12. Elman, C. (2005). Explanatory typologies in qualitative studies of international politics. International Organization, 59, 293-326.
13. Erikson, R., & Goldthorpe, J.H. (1993). The constant flux. Oxford: Clarendon Press.
14. Freedman, D.A. (1987). As others see us: A case study in path analysis. Journal of Educational Statistics, 12(2), 101-128.
15. George, A.L., & Bennett, A. (2005). Case studies and theory development in the social sciences. Cambridge, MA: MIT Press.
16. Glaesser, J. (2008). Just how flexible is the German selective secondary school system? A configurational analysis. International Journal of Research and Method in Education, 31(2), 193-209.
17. Goldthorpe, J.H. (1997). Current issues in comparative macrosociology: A debate on methodological issues. Comparative Social Research, 16, 1-26.
18. Kosko, B. (1994). Fuzzy thinking. London: Harper Collins.
19. Kruse, R., Doring, C., & Lesot M.-J. (2007). Fundamentals of fuzzy clustering. In J.V. de Oliveira & W. Pedrycz (Eds.), Advances in fuzzy clustering and its applications (pp. 3-30). New York: Wiley.
20. Kvist, J. (2007). Fuzzy set ideal type analysis. Journal of Business Research, 60, 474-481.
21. Lattin, J.M., Carroll, J.D., & Green, P.E. (2003). Analyzing multivariate data. Pacific Grove, CA: Thomson Brooks.
22. Lieberson, S. (1985). Making it count. Berkeley, CA: University of California Press.
23. Mahoney, J. (2008). Toward a unified theory of causality. Comparative Political Studies, 41(4/5), 412-436.
24. Mahoney, J., & Goertz, G. (2006). A tale of two cultures: Contrasting quantitative and qualitative research. Political Analysis, 14(3), 227-249.
25. Pawson, R. (1989). A measure for measures. London: Routledge.
26. Pedrycz, W. (2005). Knowledge-based clustering. New York: Wiley.
27. Pisces Conservation Ltd. (2005). Fuzzy grouping 2: Manual. Lymington: Author.
28. Ragin, C.C. (2000). Fuzzy set social science. Chicago: Chicago University Press.
29. Ragin, C.C. (2004). From fuzzy sets to crisp truth tables. Retrieved May 4, 2010, from, http://www.compasss.org/files/WPfiles/Raginfztt_April05.pdf
30. Ragin, C.C. (2006a). Set relations in social research: Evaluating their consistency and coverage. Political Analysis, 14, 291-310.
31. Ragin, C.C. (2006b). The limitations of net-effects thinking. In B. Rihoux & H. Grimm (Eds.), Innovative comparative methods for policy analysis (pp. 13-41). New York: Springer.
32. Ragin, C.C. (2008). Redesigning social inquiry. Chicago: University of Chicago Press.
33. Ragin, C.C., & Becker, H.S. (1992). What is a case? Cambridge: Cambridge University Press.
34. Ragin, C.C., Drass, K.A., & Davey, S. (2006). Fuzzy-set/qualitative comparative analysis 2.0. Tucson, AZ: Department of Sociology, University of Arizona.
35. Ragin, C.C., Rubinson, C, Schaefer, D., Anderson, S., Williams, E., & Giesel, H. (2006). User's guide to fuzzy-set/qualitative comparative analysis 2.0. Tucson, AZ: Department of Sociology, University of Arizona.
36. Smithson, M.J. (1987). Fuzzy set analysis for behavioral and social sciences. New York: Springer-Verlag.
37. Uprichard, E., Burrows, R., & Byrne, D. (2008). SPSS as an 'inscription device': From causality to description? Sociological Review, 56(4), 606-622.
38. Verkuilen, J. (2005). Assigning membership in a fuzzy set analysis. Sociological Methods and Research, 33(4), 462-496.
39. Wiggins, R.D., Erzberger, C., Hyde, M., Higgs, P., & Blane, D. (2007). Optimal matching analysis using ideal types to describe the lifecourse: An illustration of how histories of work, partnerships and housing relate to quality of life in early old age. International Journal of Social Research Methodology, 10(4), 259-278.