Continuous measurement makes small coding errors flip necessity or sufficiency results

Evidence

Once we move to fuzzy-set scores, however, it becomes more difficult to evaluate success and failure. The use of continuous fuzzy-set scores increases the probability that small coding errors will lead one or more cases to violate sufficiency or necessity. Since we have a complex model and only approximate codings for the secondary-level variables, it is quite likely that our test will produce one or more false negatives. Hence, we will consider a case to be consistent with causal sufficiency (or necessity) if its fuzzy-set value on the cause (or outcome) exceeds its score on the outcome (or cause) by no more than one fuzzy membership unit, which in our coding scheme means a difference of no more than . (Ragin 2000). — Gary Goertz, Social Science Concepts, 1742

Categorization

• DEEPTHINKING: The core epistemic problem: any strict set-theoretic test of a fuzzy model can be broken by noise, so tolerance thresholds become a substantive methodological choice, not a technicality.