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Exploring the robustness of set theoretic findings from a large n fsQCA: an illustration from the sociology of education.
- Source :
- International Journal of Social Research Methodology; Jul2016, Vol. 19 Issue 4, p445-459, 15p, 1 Diagram, 7 Charts
- Publication Year :
- 2016
-
Abstract
- Ragin’s Qualitative Comparative Analysis (QCA) is often used with small to medium samples where the researcher has good case knowledge. Employing it to analyse large survey datasets, without in-depth case knowledge, raises new challenges. We present ways of addressing these challenges. We first report a single QCA result from a configurational analysis of the British National Child Development Study dataset (highest educational qualification as a set theoretic function of social class, sex and ability). We then address the robustness of our analysis by employing Duşa and Thiem’s R QCA package to explore the consequences of (i) changing fuzzy set theoretic calibrations of ability, (ii) simulating errors in measuring ability and (iii) changing thresholds for assessing the quasi-sufficiency of causal configurations for educational achievement. We also consider how the analysis behaves under simulated re-sampling, using bootstrapping. The paper offers suggested methods to others wishing to use QCA with large n data. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13645579
- Volume :
- 19
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- International Journal of Social Research Methodology
- Publication Type :
- Academic Journal
- Accession number :
- 118192903
- Full Text :
- https://doi.org/10.1080/13645579.2015.1033799