Methodological Innovations (Aug 2011)
Selecting Cases for in-Depth Study from a Survey Dataset: An Application of Ragin's Configurational Methods
Abstract
While ‘establishing the phenomena’, to use Merton's phrase, is an important part of the sociological enterprise, in then accounting for such empirical regularities, theoretical models are required to understand causal processes. Both regression analysis and configurational methods applied to large datasets can establish patterns of relationships. Following a realist view, we assume that causal mechanisms have generated such patterns, and sound theoretical models are required to understand them. In-depth case studies can contribute to advancing such causal knowledge. We describe how, in the particular context of the configurational mode of analysis that characterises Ragin's Qualitative Comparative Analysis (QCA), we have selected individuals for in-depth study with the eventual purpose of advancing causal or explanatory understanding of conjunctural empirical regularities concerning educational careers. While forms of regression analysis seek to establish the net effects of ‘independent’ variables, QCA, employing Boolean algebra, analyses the conjunctions of conditions sufficient and/or necessary for an outcome to occur. QCA aims to preserve, holistically, the features of cases and is therefore well-suited to case selection. We use QCA both to undertake an initial large scale cross-case analysis and to subsequently select cases to develop theoretical understanding via within-case analysis. Using QCA's measures of consistency with relations of sufficiency and necessity, we can classify cases as typical and deviant, with these two types of cases playing different roles in testing and developing theory. Drawing on analyses of the German SOEP dataset undertaken as part of a larger study which is applying case-based configurational methods to English and German survey datasets while undertaking subsequent in-depth interviews with selected cases, we demonstrate how QCA can be used to select cases for interview in a systematic and theoretically informed manner.