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oai:riuma.uma.es:10630/401532026-02-03T10:49:57Zcom_10630_2254col_10630_37953

Blanca-Mena, María José Bono Cabré, Roser Arnau, Jaume García-Castro, F. Javier Alarcón-Postigo, Rafael Vallejo, Guillermo 2025-10-09T11:40:39Z 2025-10-09T11:40:39Z 2025 Blanca, M. J., Bono, R., Arnau, J., Alarcón, R., García-Castro, F. J., & Vallejo, G. (2025). When to use Bootstrap-F in One-Way Repeated Measures ANOVA: Type I Error and Power. Psicothema, 37(3), 12-22. https://doi.org/10.70478/psicothema.2025.37.20 https://hdl.handle.net/10630/40153 10.70478/psicothema.2025.37.20 Background: With repeated measures, the traditional ANOVA F-statistic requires fulfillment of normality and sphericity. Bootstrap-F (B-F) has been proposed as a procedure for dealing with violation of these assumptions when conducting a one-way repeated measures ANOVA. However, evidence regarding its robustness and power is limited. Our aim is to extend knowledge about the behavior of B-F with a wider range of conditions. Method: A simulation study was performed, manipulating the number of repeated measures, sample sizes, epsilon values, and distribution shape. Results: B-F may become conservative with higher values of epsilon, and liberal under extreme violation of both normality and sphericity and small sample sizes. In these cases, B-F may be used with a more stringent alpha level (.025). The results also show that power is affected by sphericity: the lower the epsilon value, the larger the sample size required to ensure adequate power. Conclusions: B-F is robust under non-normality and non-sphericity with sample sizes larger than 20-25. eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Psicología - Metodología Análisis de varianza When to use Bootstrap-F in One-Way Repeated Measures ANOVA: Type I Error and Power. journal article