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Multilevel Exploratory Factor Analysis (ML-EFA)×Exploratieve factoranalyse (EFA)×
VakgebiedPsychometrieStatistiek
FamilieLatent structureLatent structure
Jaar van ontstaan1994
GrondleggerBengt O. Muthén
TypeLatent variable / multilevel dimension reductionLatent variable / dimension reduction
Oorspronkelijke bronMuthén, B. O. (1994). Multilevel covariance structure analysis. Sociological Methods & Research, 22(3), 376–398. DOI ↗Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. DOI ↗
AliassenML-EFA, multilevel factor analysis, two-level exploratory factor analysis, hierarchical exploratory factor analysiscommon factor analysis, açımlayıcı faktör analizi, factor analysis
Verwant34
SamenvattingMultilevel exploratory factor analysis uncovers latent factor structures simultaneously at two or more levels of a data hierarchy — for example, both within individuals and between groups — without imposing a fixed structure in advance. It is essential whenever survey or test items are collected from respondents nested inside classrooms, organisations, or clinics.Exploratory factor analysis reduces a large set of observed variables into a smaller number of latent common factors. It is widely used in scale development and psychometrics to uncover the dimensional structure that underlies a set of correlated items, without specifying that structure in advance.
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ScholarGateMethoden vergelijken: Multilevel EFA · EFA. Geraadpleegd op 2026-06-15 via https://scholargate.app/nl/compare