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Analys av statistisk styrka för multilevel- och blandade modeller×Envägs variansanalys×
ÄmnesområdeStatistikStatistik
FamiljHypothesis testHypothesis test
Ursprungsår19931925
UpphovspersonSnijders & Bosker; Hox, Moerbeek & van de SchootRonald A. Fisher
TypSample-size planning for hierarchical designsParametric mean comparison
UrsprungskällaSnijders, T.A.B. & Bosker, R.J. (2012). Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling (2nd ed.). SAGE. ISBN: 978-1849202015Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗
AliasHLM power analysis, mixed-effects power analysis, clustered design power analysis, Çok Düzeyli / Karma Model Güç Analizione-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA
Närliggande44
SammanfattningMultilevel 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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ScholarGateJämför metoder: Multilevel Power Analysis · One-way ANOVA. Hämtad 2026-06-18 från https://scholargate.app/sv/compare