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Multilevel Exploratory Factor Analysis (ML-EFA)×Explorativ faktoriell analys (EFA)×
ÄmnesområdePsykometriStatistik
FamiljLatent structureLatent structure
Ursprungsår1994
UpphovspersonBengt O. Muthén
TypLatent variable / multilevel dimension reductionLatent variable / dimension reduction
UrsprungskällaMuthén, 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 ↗
AliasML-EFA, multilevel factor analysis, two-level exploratory factor analysis, hierarchical exploratory factor analysiscommon factor analysis, açımlayıcı faktör analizi, factor analysis
Närliggande34
SammanfattningMultilevel 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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ScholarGateJämför metoder: Multilevel EFA · EFA. Hämtad 2026-06-15 från https://scholargate.app/sv/compare