Qualitative Comparative Analysis

Abstract

Qualitative Comparative Analysis (QCA) is the core method employed throughout this book, both in the cross-case analysis of large n data sets and as the basis of the construction of the typologies of cases from which interviewees were chosen for in-depth study. It was developed by Charles Ragin (Ragin, 1987, 2000, 2008), with one of its first applied fields being political sciences, and it has since been used in other social science contexts. Originally mainly used with small to medium n samples, it has been usefully employed with large n (for example, Cooper, 2005; Fiss, 2011; Glaesser, 2008; Glaesser & Cooper, 2011b; Ragin, 2006a). Drawing on set theory, Boolean logic and algebra and the concepts of necessary and sufficient conditions, QCA offers a systematic way of analysing small to medium n data, and it can provide an alternative to regression-based methods for large n analysis. In regression approaches, the focus is on estimating the net effects of independent variables, while controlling for others (Ragin, 2006a). QCA, rather than focussing on net effects, explores the various ways in which the factors under study combine to produce some outcome. QCA is well suited to analysing such conjunctions of conditions and, in addition, to situations where there are several pathways to the outcome.