手法を比較

	多層確認的因子分析 (MCFA)	潜在プロフィール分析 (LPA)
分野	心理測定学	心理測定学
系統	Latent structure	Latent structure
提唱年	1994	2010
提唱者	Bengt O. Muthen	Lazarsfeld & Henry; Collins & Lanza
種類	Latent variable model / measurement model	Person-centered finite mixture model
原典	Muthen, B. O. (1994). Multilevel covariance structure analysis. Sociological Methods & Research, 22(3), 376–398.	Collins, L. M., & Lanza, S. T. (2010). Latent Class and Latent Transition Analysis. Wiley. ISBN: 978-0-470-22839-7
別名	MCFA, multilevel measurement model, two-level CFA, hierarchical CFA	Continuous Latent Class Analysis, Gaussian Profile Mixture Model, Person-Centered Cluster Analysis, Gizil Profil Analizi
関連	6	2
概要	Multilevel confirmatory factor analysis tests a pre-specified factor structure while simultaneously accounting for the non-independence of observations caused by clustered data. It decomposes item variance into within-group and between-group components, fitting a separate measurement model at each level, making it the standard tool for validating psychometric scales administered within natural groups such as classrooms, clinics, or organisations.	Latent Profile Analysis (LPA) is a person-centered finite mixture modeling technique that identifies unobserved subgroups — called profiles — within a population based on patterns of scores across multiple continuous indicators. Rooted in Lazarsfeld and Henry's latent structure tradition and formally synthesized for applied behavioral research by Collins and Lanza (2010), LPA assumes that observed heterogeneity in continuous data arises from a discrete number of latent classes, each characterized by a unique multivariate mean profile.