Coincidence Analysis (CNA) traditionally analyzes dichotomous variables. This paper extends its capabilities to multi-value and fuzzy-set data, offering enhanced inferential power for complex political phenomena.

Dataset Expansion: The generalized approach accommodates continuous variables interpreted as membership scores in fuzzy sets.

Multi-Outcome Advantage: CNA now excels at identifying causal structures across multiple outcomes—a capability QCA lacks.

Methodological Comparison: This adaptation provides superior analytical tools even for single-outcome scenarios, where QCA typically operates.

Practical Application: The new techniques are implemented in the R package cna's latest version.