Comparar métodos

	Análisis de potencia para modelos multinivel y de efectos mixtos	Análisis de potencia para ANOVA
Campo	Estadística	Estadística
Familia	Hypothesis test	Hypothesis test
Año de origen	1993	1988
Autor original	Snijders & Bosker; Hox, Moerbeek & van de Schoot	Jacob Cohen
Tipo	Sample-size planning for hierarchical designs	Sample size determination
Fuente seminal	Snijders, T.A.B. & Bosker, R.J. (2012). Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling (2nd ed.). SAGE. ISBN: 978-1849202015	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832
Alias	HLM power analysis, mixed-effects power analysis, clustered design power analysis, Çok Düzeyli / Karma Model Güç Analizi	ANOVA power analysis, F-test power analysis, sample size for ANOVA, Güç Analizi — ANOVA
Relacionados	4	4
Resumen	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.	Power analysis for ANOVA is a prospective statistical technique that determines the minimum sample size needed to detect a specified group mean difference with a chosen probability. Formalized by Jacob Cohen in his 1988 monograph, it translates a researcher's effect size expectation — expressed as Cohen's f — along with the desired Type I error rate (alpha) and statistical power (1 − beta) into a concrete per-group sample size recommendation for one-way or factorial ANOVA designs.