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When to use Bootstrap-F in one-way repeated measures ANOVA: Type I error and power

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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.

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Facultad de Psicología de la Universidad de Oviedo y el Colegio Oficial de Psicólogos del Principado de Asturias

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Articles publicats en revistes (Psicologia Social i Psicologia Quantitativa)

# metadata.dc.title[].value
When to use Bootstrap-F in one-way repeated measures ANOVA: Type I error and power

# metadata.dc.title.alternative[].value
Cuándo Usar F-Bootstrap en ANOVA Unifactorial de Medidas Repetidas: Error de Tipo I y Potencia