Compara mètodes

	Anàlisi Factorial Confirmatòria (CFA)	Modelització d'equacions estructurals
Camp	Psicometria	Estadística per a la recerca
Família	Latent structure	Process / pipeline
Any d'origen	1969	1921
Autor original	Karl Gustav Jöreskog	Sewall Wright
Tipus	Hypothesis-testing latent variable model	Method
Font seminal	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.	Jöreskog, K. G., & Sörbom, D. (1973). LISREL: A general computer program for estimating a linear structural equation system. Research Bulletin 73-5. University of Stockholm.
Àlies	CFA, confirmatory FA, measurement model, restricted factor analysis	SEM, path analysis, latent variable modeling, causal modeling
Relacionats	4	3
Resum	Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing.	Structural equation modeling (SEM) is a comprehensive statistical framework combining path analysis (Sewall Wright, 1921) and confirmatory factor analysis to test complex causal models linking observed and latent variables. Formalized by Jöreskog (1973) with LISREL software, SEM enables simultaneous estimation of measurement relationships (how variables measure latent constructs) and structural relationships (how constructs influence outcomes), making it powerful for theory testing in psychology, epidemiology, organizational research, and health sciences where complex mediation, moderation, and latent processes require integrated analysis.