Qualitative comparative analysis (QCA) uses Boolean algebra to offer an alternative to conventional statistical techniques for analyzing empirical data. While large-N representative applications of QCA are increasingly popular, QCA is especially useful for identifying and understanding cross-case patterns in small- and medium-N projects with data collected using qualitative and/or mixed methods. Fundamentally a pattern-matching technique designed for exploring the differences and diversity within one’s data, QCA may be used for uncovering empirical taxonomies, analyzing the effects of context, and identifying combinations of conditions that are necessary and/or sufficient for the occurrence (or prevention) of an outcome.

Although first developed for social and policy research during the late-1980s and 1990s, QCA is discipline-agnostic and has been successfully applied to research in such diverse areas as business management, comparative history, education, environmental studies, health services, legal studies, narrative analysis, organizational studies, policy evaluation, psychology, public health, and medicine. This workshop will provide an introduction to QCA, discussing the questions it is designed to answer, the type of data it uses, the basic steps involved in performing QCA, and how to interpret results. Software for conducting QCA and resources for further study will also be reviewed. By the end of the workshop, attendees will be able to assess whether or not QCA would be helpful for their next research project. Access to the workshop is included with registration to the conference.