Methoden vergleichen

	Multivariate Modelltestforschung	Bestätigende Faktorenanalyse (CFA)
Fachgebiet	Forschungsdesign	Psychometrie
Familie	Process / pipeline	Latent structure
Entstehungsjahr	1970s–1980s (multivariate model testing as a distinct approach)	1969
Urheber	Karl Jöreskog (SEM/LISREL framework); Barbara Tabachnick & Linda Fidell (multivariate methods synthesis)	Karl Gustav Jöreskog
Typ	Quantitative confirmatory research design	Hypothesis-testing latent variable model
Wegweisende Quelle	Tabachnick, B. G., & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Aliasnamen	multivariate model testing, multivariate structural testing, multivariate confirmatory modeling, MVMT research	CFA, confirmatory FA, measurement model, restricted factor analysis
Verwandt	5	4
Zusammenfassung	Multivariate model testing research is a confirmatory quantitative design in which a theoretically derived model involving multiple variables and their interrelationships is formally tested against empirical data. Rather than exploring patterns inductively, the researcher specifies a model a priori — capturing hypothesized directional paths, latent constructs, or covariance structures — and then evaluates how well this model reproduces the observed data using techniques such as structural equation modeling, confirmatory factor analysis, or multivariate path analysis.	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.