手法を比較

	階層的探索的因子分析 (ML-EFA)	二因子モデル（一般因子と特定因子）
分野	心理測定学	心理測定学
系統	Latent structure	Latent structure
提唱年	1994	1937
提唱者	Bengt O. Muthén	Holzinger & Swineford (1937); modern revival by Reise (2012)
種類	Latent variable / multilevel dimension reduction	Confirmatory latent variable model
原典	Muthén, B. O. (1994). Multilevel covariance structure analysis. Sociological Methods & Research, 22(3), 376–398.	Reise, S. P. (2012). The Rediscovery of Bifactor Measurement Models. Multivariate Behavioral Research, 47(5), 667–696.
別名	ML-EFA, multilevel factor analysis, two-level exploratory factor analysis, hierarchical exploratory factor analysis	Bifaktör Modeli — Genel ve Spesifik Faktörler, hierarchical factor model, general-specific factor model, Schmid-Leiman model
関連	3	6
概要	Multilevel 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.