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Analyse des conditions nécessaires×Modélisation Exploratoire par Équations Structurelles×
DomainePsychométriePsychométrie
FamilleLatent structureLatent structure
Année d'origine20162009
Auteur d'origineJan DulTihomir Asparouhov, Bengt Muthén
TypeSet-theoretic configurational analysisHybrid exploratory-confirmatory factor modeling
Source fondatriceDul, J. (2016). Necessary Condition Analysis (NCA): Logic and methodology of "necessary but not sufficient" causality. Organizational Research Methods, 19(1), 10-52. DOI ↗Asparouhov, T., & Muthén, B. (2009). Exploratory structural equation modeling. Structural Equation Modeling, 16(3), 397-438. DOI ↗
AliasNCAESEM
Apparentées55
RésuméNecessary 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.Exploratory Structural Equation Modeling (ESEM) is a hybrid approach that combines exploratory factor analysis (EFA) with confirmatory factor analysis (CFA) and path modeling, developed by Asparouhov and Muthén (2009). ESEM relaxes restrictive zero-loading assumptions of traditional CFA, allowing all indicators to load on all factors, which can reveal cross-factor complexity and improve model fit while retaining the ability to test substantive structural theories.
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ScholarGateComparer des méthodes: Necessary Condition Analysis · Exploratory Structural Equation Modeling. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare