Exploring the robustness of set theoretic findings from a large n fsQCA: an illustration from the sociology of education. Issue 4 (3rd July 2016)

• Record Type: Journal Article
• Authors: Cooper, Barry; Glaesser, Judith
• Is Part Of: International journal of social research methodology. Volume 19:Issue 4(2016)
• Page Start: 445
• Page End: 459
• Publication Date: 2016-07-03
• Subjects: Qualitative Comparative Analysis -- calibration -- fuzzy sets -- robustness -- simulation -- bootstrapping; Sociology -- Research -- Periodicals; 300.72
• DOI: 10.1080/13645579.2015.1033799
• Languages: English
• ISSNs: 1364-5579

Abstract

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.