Comparar métodos

	Análisis Factorial Confirmatorio Multinivel (MCFA)	Análisis de Perfiles Latentes (LPA)
Campo	Psicometría	Psicometría
Familia	Latent structure	Latent structure
Año de origen	1994	2010
Autor original	Bengt O. Muthen	Lazarsfeld & Henry; Collins & Lanza
Tipo	Latent variable model / measurement model	Person-centered finite mixture model
Fuente seminal	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
Alias	MCFA, multilevel measurement model, two-level CFA, hierarchical CFA	Continuous Latent Class Analysis, Gaussian Profile Mixture Model, Person-Centered Cluster Analysis, Gizil Profil Analizi
Relacionados	6	2
Resumen	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.