A bootstrapped robustness assessment for qualitative comparative analysis

C. Ben Gibson and Burrel Vann Jr

The Journal of Mathematical Sociology, 2025, vol. 49, issue 3, 147-174

Abstract: Qualitative Comparative Analysis (QCA) has been increasingly used in recent years due to its purported construction of a middle path between case-oriented and variable-oriented methods. Despite its popularity, a key element of the method has been criticized for possibly not distinguishing random from real patterns in data, rendering its usefulness questionable. QCA methodologists have suggested certain quantitative thresholds to protect against spurious results. We test the effectiveness of these thresholds using repeated random sampling of data. We find evidence for the effectiveness of these thresholds, but this effectiveness is attenuated by basic properties of the underlying data. Using the intuition of the bootstrap, we develop techniques to determine which QCA thresholds are most appropriate for the input data. This assessment can be used as a hypothesis test for QCA, with an interpretation similar to a p-value.

Date: 2025
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DOI: 10.1080/0022250X.2025.2496154

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