Methoden vergleichen

	Faktorenanalyse	Strukturelle Gleichungsmodellierung
Fachgebiet	Forschungsstatistik	Forschungsstatistik
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	1931	1921
Urheber	Louis Leon Thurstone	Sewall Wright
Typ	Method	Method
Wegweisende Quelle	Thurstone, L. L. (1947). Multiple Factor Analysis. University of Chicago Press.	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.
Aliasnamen	EFA, CFA, latent variable modeling	SEM, path analysis, latent variable modeling, causal modeling
Verwandt	3	3
Zusammenfassung	Factor analysis is a statistical technique for identifying latent (unobserved) dimensions underlying observed variables, developed by Louis Leon Thurstone in the 1930s and formalized by Jöreskog (1969). Exploratory factor analysis (EFA) discovers unknown factor structure from data; confirmatory factor analysis (CFA) tests hypothesized relationships between observed and latent variables. Essential in psychometrics (test development), organizational research (measuring constructs like leadership style), and biomedicine (identifying disease subtypes), factor analysis reduces dimensionality while revealing conceptual organization in multivariate data.	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.