The R Manual for QCA has been updated to version 4.1 (August 2026). Among other changes, the manual now includes expanded sections on visualizing QCA results, with templates for creating, customizing, and combining X–Y plots and saving graphics as PDF or PNG files. There are also new sections on cluster analysis and robustness tests. The robustness tests follow the protocol developed by Oana and Schneider (2024), illustrated with replication data from a published study (Meissner and Mello 2022).

While the R Manual is written to get readers started, without assuming prior knowledge of R, it has grown into a 44-page document that provides step-by-step instructions for a complete QCA research cycle, from data management and calibration to necessary conditions, truth table analysis, solution types, and the visualization of results. All code is included in an accompanying R Script that can be adapted for one’s own purposes, complemented by two sample data sets. The analyses draw on the QCA package by Adrian Duşa and the SetMethods package by Ioana-Elena Oana and Carsten Q. Schneider, together with ggplot2 and further packages for visualization. For comprehensive treatments of QCA in R, see Duşa’s QCA with R (Springer, 2019) and Oana, Schneider, and Thomann’s Qualitative Comparative Analysis Using R (Cambridge University Press, 2021).

The R Manual for QCA (PDF file, R Script, and sample data) can be downloaded here and on Harvard Dataverse: https://doi.org/10.7910/DVN/KYF7VJ.