Exploring the robustness of set theoretic findings from a large n fsQCA: an illustration from the sociology of education |
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Authors: | Barry Cooper Judith Glaesser |
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Institution: | School of Education, Durham University, Leazes Road, Durham DH1 1TA, UK |
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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 Du?a 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. |
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Keywords: | Qualitative Comparative Analysis calibration fuzzy sets robustness simulation bootstrapping |
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