Сравнение методов

	Конфирматорный факторный анализ (КФА)	Структурное моделирование (Structural Equation Modeling)
Область	Психометрия	Статистика исследований
Семейство	Latent structure	Process / pipeline
Год появления	1969	1921
Автор метода	Karl Gustav Jöreskog	Sewall Wright
Тип	Hypothesis-testing latent variable model	Method
Основополагающий источник	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.
Другие названия	CFA, confirmatory FA, measurement model, restricted factor analysis	SEM, path analysis, latent variable modeling, causal modeling
Связанные	4	3
Сводка	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.