ScholarGate
Assistent

Methoden vergelijken

Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.

Noodzakelijkheidsanalyse×Partial Least Squares Structurele Vergelijkingsmodeling×
VakgebiedPsychometriePsychometrie
FamilieLatent structureLatent structure
Jaar van ontstaan20161985
GrondleggerJan DulHerman Wold
TypeSet-theoretic configurational analysisComponent-based structural equation model
Oorspronkelijke bronDul, J. (2016). Necessary Condition Analysis (NCA): Logic and methodology of "necessary but not sufficient" causality. Organizational Research Methods, 19(1), 10-52. DOI ↗Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). Sage Publications. ISBN: 9781483377445
AliassenNCAPLS-SEM, PLS path modeling
Verwant55
SamenvattingNecessary 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.PLS-SEM is a variance-based approach to structural equation modeling developed by Herman Wold (1985) that estimates latent variable models by maximizing the variance explained in dependent variables. Unlike covariance-based SEM, PLS-SEM is particularly useful for exploratory research, small to medium samples, complex models with many constructs, and non-normal data.
ScholarGateGegevensset
  1. v1
  2. 3 Bronnen
  3. PUBLISHED
  1. v1
  2. 3 Bronnen
  3. PUBLISHED

Naar zoeken Dia's downloaden

ScholarGateMethoden vergelijken: Necessary Condition Analysis · Partial Least Squares Structural Equation Modeling. Geraadpleegd op 2026-06-17 via https://scholargate.app/nl/compare