Using case‐based approaches to analyse large datasets: a comparison of Ragin's fsQCA and fuzzy cluster analysis
International Journal of Social Research Methodology
2011) '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). pp. 31-48. This is an electronic version of an article published in Cooper, B. and Glaesser, J. (2011) '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). pp. 31-48. International
... International journal of social research methodology is available online at: http://www.informaworld.com/smpp/ with the open URL of your article. Additional information: Use policy The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-profit purposes provided that: • a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders. Please consult the full DRO policy for further details. Abstract The paper undertakes a comparison of Ragin"s fuzzy set Qualitative Comparative Analysis with cluster analysis. After describing key features of both methods, it uses a simple invented example to illustrate an important algorithmic difference in the way in which these methods classify cases. It then examines the consequences of this difference via analyses of data previously calibrated as fuzzy sets. The data, taken from the National Child Development Study, concern educational achievement, social class, ability and gender. The classifications produced by fsQCA and fuzzy cluster analysis (FCA) are compared and the reasons for the observed differences between them are discussed. The predictive power of both methods is also compared, employing both correlational and set theoretic comparisons, using highest qualification achieved as the outcome. In the main, using the real data, the two methods are found to produce similar results. A final discussion considers the generalisability or otherwise of this finding.