It Might Look like a Regression Equation ... but It’s Not! an Intuitive Approach to the Presentation of Qca Results

QCA and fsQCA methods were devised to offer a qualitative approach to research that allows for the handling of multiple cases and multiple causation. Non-specialists reviewing papers written using QCA or fsQCA techniques often encounter considerable difficulties in interpreting the results. A key problem is that those not trained in these approaches may try to make sense of findings by analogy to the more standard statistical approaches with which they were already familiar, and thus get misled. In this essay we focus on five graphical and tabular display techniques for QCA or fsQCA results and how each (a) displays relations between variables; (b) highlights descriptive or causal accounts for specific (groups of) cases; (c) expresses the degree of fit. We also consider how each technique may have a “false friend” in the standard statistics literature with which it can too easily be confused. Acknowledgement: A previous version of this paper has been presented at the conference “Comparative Politics: Empirical Applications of Methodological Innovations”, Sophia University, Tokyo (Japan), 15. 17. July 2006. The authors like to thank participants in this conference for their comments. The usual disclaimers apply.