Today quantitative social science is dominated by analytic methods that are heavily slanted toward “variables.” The key focus of analysis is the assessment of the relative importance of “independent” variables on a dependent variable, and researchers view their central task as estimating “net effects.” Many scholars find the dominance of variable-oriented approaches deplorable and argue that the proper remedy is to drop the variable altogether from the lexicon of social research. I argue, however, that the notion of the variable should be reformulated in ways that enhance the interplay and integration of cross-case and within-case analysis. Central to this reformulation is set-theoretic methods such as truth table analysis. I show that set-theoretic methods not only provide a better way for researchers to study “connections” between aspects of cases, it also offers a better bridge to conceptual discourse. I argue further that the extensions and elaborations of set-theoretic methods that are afforded by the use of fuzzy sets are especially valuable for social research.
In this talk, Charles C. Ragin argues that the notion of the variable in quantitative social science should be reformulated in ways that enhance the interplay and integration of cross-case and within-case analysis.