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| Cronbachs Alpha (Reliabilitätsanalyse)× | Bestätigende Faktorenanalyse (CFA)× | Strukturelle Gleichungsmodellierung (SEM)× | |
|---|---|---|---|
| Fachgebiet≠ | Statistik | Psychometrie | Statistik |
| Familie | Latent structure | Latent structure | Latent structure |
| Entstehungsjahr≠ | 1951 | 1969 | 1970 |
| Urheber≠ | Lee J. Cronbach | Karl Gustav Jöreskog | Karl Jöreskog (LISREL framework, 1970s) |
| Typ≠ | Reliability / internal consistency coefficient | Hypothesis-testing latent variable model | Latent variable / causal modeling |
| Wegweisende Quelle≠ | Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ | Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540 |
| Aliasnamen | coefficient alpha, alpha reliability, internal consistency reliability, Güvenilirlik Analizi (Cronbach Alpha) | CFA, confirmatory FA, measurement model, restricted factor analysis | Yapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling |
| Verwandt≠ | 4 | 4 | 5 |
| Zusammenfassung≠ | Cronbach's alpha is a coefficient of internal consistency that quantifies the degree to which a set of items on a scale measures the same underlying construct. Introduced by Lee J. Cronbach in 1951, it remains the most widely reported reliability index in social-science, health, and educational research. | 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 is a multivariate statistical framework that simultaneously estimates a measurement model — relating observed indicators to latent constructs — and a structural model specifying directional or reciprocal relationships among those constructs. Rooted in the LISREL tradition developed by Karl Jöreskog in the 1970s, SEM is the standard tool for testing complex theoretical models in the social, behavioural, and management sciences. |
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