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| Bayesian Cronbachs Alpha× | Generalisierbarkeitstheorie (G-Theorie)× | |
|---|---|---|
| Fachgebiet | Psychometrie | Psychometrie |
| Familie | Latent structure | Latent structure |
| Entstehungsjahr≠ | 2011 (Bayesian form); 1951 (classical alpha) | 1963–1972 |
| Urheber≠ | Padilla & Zhang (Bayesian adaptation); Cronbach (classical alpha, 1951) | Lee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam |
| Typ≠ | Bayesian reliability estimation | Variance-components reliability model |
| Wegweisende Quelle≠ | Padilla, M. A., & Zhang, G. (2011). Estimating internal consistency using Bayesian methods. Journal of Modern Applied Statistical Methods, 10(1), 277–286. DOI ↗ | Cronbach, L. J., Gleser, G. C., Nanda, H. & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. Wiley. link ↗ |
| Aliasnamen≠ | Bayesian alpha, Bayesian internal consistency, Bayes-alpha, posterior alpha | G-theory, G-study / D-study framework, variance components reliability |
| Verwandt≠ | 2 | 4 |
| Zusammenfassung≠ | Bayesian Cronbach's alpha applies Bayesian inference to estimate the classical internal-consistency coefficient, yielding a full posterior distribution over alpha rather than a single point estimate. This allows researchers to quantify uncertainty with credible intervals and incorporate prior knowledge, making reliability assessment more informative — especially with small or skewed samples. | Generalizability Theory is a psychometric framework that decomposes observed score variance into multiple sources — persons, items, raters, occasions, and their interactions — using analysis of variance. It replaces the single reliability coefficient of classical test theory with a family of coefficients that tell researchers how well scores generalize across different measurement conditions. |
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