Abstract
The usual QCA data is numeric, and has specific formats for each flavour: when crisp (either binary or multi-value) the data consists of integers starting from the value of 0, and when fuzzy the values span over a continuous range, anywhere between 0 and 1.
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Notes
- 1.
This term should not be confused with the log odds in the logistic regression (aka “logit”), that is the natural logarithm of the “odds ratio”.
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Duşa, A. (2019). Calibration. In: QCA with R. Springer, Cham. https://doi.org/10.1007/978-3-319-75668-4_4
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