Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Analyse de puissance pour les modèles multiniveaux et à effets mixtes× | Analyse de variance à un facteur× | |
|---|---|---|
| Domaine | Statistique | Statistique |
| Famille | Hypothesis test | Hypothesis test |
| Année d'origine≠ | 1993 | 1925 |
| Auteur d'origine≠ | Snijders & Bosker; Hox, Moerbeek & van de Schoot | Ronald A. Fisher |
| Type≠ | Sample-size planning for hierarchical designs | Parametric mean comparison |
| Source fondatrice≠ | Snijders, T.A.B. & Bosker, R.J. (2012). Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling (2nd ed.). SAGE. ISBN: 978-1849202015 | Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗ |
| Alias | HLM power analysis, mixed-effects power analysis, clustered design power analysis, Çok Düzeyli / Karma Model Güç Analizi | one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA |
| Apparentées | 4 | 4 |
| Résumé≠ | Multilevel power analysis is a sample-size planning procedure designed for hierarchical, clustered, or longitudinal study designs in which observations are nested within higher-level units such as students within schools or patients within clinics. Formalized in the multilevel modeling literature by Snijders and Bosker (1993, expanded 2012) and Hox, Moerbeek, and van de Schoot (2017), it accounts for the intraclass correlation (ICC) and the design effect that arises when data are clustered, ensuring that both the number of clusters and the cluster size are adequate to detect a target effect. | One-way ANOVA is a parametric hypothesis test that compares the means of three or more independent groups on a single continuous outcome to decide whether at least one group mean differs. It rests on the variance-partitioning framework introduced by Ronald A. Fisher in 1925. |
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