A comprehensive introduction and teaching resource for state-of-the-art Qualitative Comparative Analysis (QCA) using R software. This guide facilitates the efficient teaching, independent learning, and use of QCA with the best available software, reducing the time and effort required when encountering not just the logic of a new method, but also new software. With its applied and practical focus, the book offers a genuinely simple and intuitive resource for implementing the most complete protocol of QCA. To make the lives of students, teachers, researchers, and practitioners as easy as possible, the book includes learning goals, core points, empirical examples, and tips for good practices. The freely available online material provides a rich body of additional resources to aid users in their learning process. Beyond performing core analyses with the R package QCA, the book also facilitates a close integration with the R package SetMethods allowing for a host of additional protocols for building a more solid and well-rounded QCA.
Correlation coefficients often used in quantitative research, such as survey research, cannot adequately measure certain key aspects within the relation of necessity. In this paper, I focus on Qualitative Comparative Analysis (QCA), enabling the analysis of set relations or relations of necessity and sufficiency, and try to incorporate it into the analysis of survey research. I present the parameters of fit in a fuzzy-set QCA to measure such a relation. I also show the methods used to conduct statistical inferences to understand the properties of a population based on a random sample from that population. For example, I analyzed the survey data on the purpose of tort damages in the case of a defective car accident in Japan. In this survey, respondents were asked about the extent to which they considered five factors in deciding the amount of damages: compensation for monetary loss, punishment, compensation for mental suffering, deterrence, and satisfying the feeling of retribution. I found that compensation for monetary loss is not correlated with punishment, deterrence, and satisfying the feeling of retribution. However, compensation for monetary loss is a necessary condition. The analysis of relations of necessity can highlight relations that have not been detected by conventional statistical analysis based on correlations.
A special issue of Quality & Quantity focusing on “Causation, inferences, and solution types in configurational comparative methods,” co-edited by Tim Haesebrouck (Ghent University) and Eva Thomann (University of Konstanz), is now available on-line. An introduction to the issue is provided below, along with the direct links to the articles, which are available in the COMPASSS bibliography.