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| Alpha de Cronbach (Analyse de fiabilité)× | Modélisation Linéaire Hiérarchique (HLM / Modélisation Multiniveaux)× | |
|---|---|---|
| Domaine | Statistique | Statistique |
| Famille≠ | Latent structure | Hypothesis test |
| Année d'origine≠ | 1951 | 1986 |
| Auteur d'origine≠ | Lee J. Cronbach | Raudenbush & Bryk (popularized); Goldstein (parallel development) |
| Type≠ | Reliability / internal consistency coefficient | Parametric nested-data regression |
| Source fondatrice≠ | Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334. DOI ↗ | Raudenbush, S.W. & Bryk, A.S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 978-0761919049 |
| Alias≠ | coefficient alpha, alpha reliability, internal consistency reliability, Güvenilirlik Analizi (Cronbach Alpha) | HLM, MLM, multilevel modeling, multilevel analysis |
| Apparentées | 4 | 4 |
| Résumé≠ | 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. | Hierarchical Linear Modeling (HLM), also known as Multilevel Modeling (MLM), is a parametric statistical method for analyzing nested or clustered data — for example students within classrooms, patients within hospitals, or employees within organizations. Formalized by Raudenbush and Bryk in their 2002 seminal text (building on work from the mid-1980s), HLM simultaneously estimates individual-level and group-level effects while correctly partitioning variance across levels. |
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