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Analisis Faktor Eksploratori Bertingkat (ML-EFA)×Model Bifaktor (Faktor Umum dan Khusus)×
BidangPsikometrikPsikometrik
KeluargaLatent structureLatent structure
Tahun asal19941937
PengasasBengt O. MuthénHolzinger & Swineford (1937); modern revival by Reise (2012)
JenisLatent variable / multilevel dimension reductionConfirmatory latent variable model
Sumber perintisMuthén, B. O. (1994). Multilevel covariance structure analysis. Sociological Methods & Research, 22(3), 376–398. DOI ↗Reise, S. P. (2012). The Rediscovery of Bifactor Measurement Models. Multivariate Behavioral Research, 47(5), 667–696. DOI ↗
AliasML-EFA, multilevel factor analysis, two-level exploratory factor analysis, hierarchical exploratory factor analysisBifaktör Modeli — Genel ve Spesifik Faktörler, hierarchical factor model, general-specific factor model, Schmid-Leiman model
Berkaitan36
RingkasanMultilevel 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.The bifactor measurement model specifies that every indicator loads simultaneously on a single general factor and on one of several specific (group) factors. Formally introduced by Holzinger and Swineford in 1937 and brought into mainstream psychometrics by Reise (2012), it is now the standard tool for evaluating whether a multidimensional scale can legitimately yield a single composite score.
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ScholarGateBandingkan kaedah: Multilevel EFA · Bifactor Model. Dicapai 2026-06-15 daripada https://scholargate.app/ms/compare