ScholarGate
Pembantu

Bandingkan kaedah

Semak kaedah pilihan anda secara bersebelahan; baris yang berbeza akan diserlahkan.

Analisis Faktor Eksploratori Bertingkat (ML-EFA)×Analisis Faktor Penerokaan (EFA)×
BidangPsikometrikStatistik
KeluargaLatent structureLatent structure
Tahun asal1994
PengasasBengt O. Muthén
JenisLatent variable / multilevel dimension reductionLatent variable / dimension reduction
Sumber perintisMuthén, 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
Berkaitan34
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.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.
ScholarGateSet data
  1. v1
  2. 2 Sumber
  3. PUBLISHED
  1. v2
  2. 2 Sumber
  3. PUBLISHED

Pergi ke carian Muat turun slaid

ScholarGateBandingkan kaedah: Multilevel EFA · EFA. Dicapai 2026-06-15 daripada https://scholargate.app/ms/compare