Latent structureNecessity-Sufficiency Analysis

Necessary Condition Analysis

Necessary Condition Analysis (NCA) is a set-theoretic method developed by Dul (2016) that identifies conditions necessary (but not necessarily sufficient) for an outcome to occur. Unlike regression, which estimates average effects, NCA identifies absolute thresholds: conditions that must be present at a certain level for the outcome to be possible, regardless of other factors.

Open in MethodMindSoonVideoSoon

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

Sources

  1. Dul, J. (2016). Necessary Condition Analysis (NCA): Logic and methodology of "necessary but not sufficient" causality. Organizational Research Methods, 19(1), 10-52. DOI: 10.1177/1094428115584005
  2. Dul, J. (2018). A strategy for dealing with flaws and limitations in quantitative research. Organizational Research Methods, 21(1), 104-125. DOI: 10.1177/1094428117725206
  3. Dul, J. (2019). Necessary Condition Analysis (NCA) version 3.3: A User Manual. Europeanstudies.org. Retrieved from https://www.erim.eur.nl/people/jan-dul/ link

Related methods

Referenced by

ScholarGateNecessary Condition Analysis (Necessary Condition Analysis). Retrieved 2026-06-04 from https://scholargate.app/en/psychometrics/necessary-condition-analysis