Datos no Normales en el ANOVA de Medidas Repetidas: Impacto en el Error Tipo I y Potencia
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Palabras clave

Violation of normality
Within-subject design
Robustness
Power
ANOVA Violación de la normalidad
Diseño intrasujeto
Robustez
Potencia
ANOVA

Cómo citar

Blanca, M. J., Arnau, J., García-Castro, F. J., Alarcón, R., & Bono, R. (2023). Datos no Normales en el ANOVA de Medidas Repetidas: Impacto en el Error Tipo I y Potencia. Psicothema, 35(1), 21–29. Recuperado a partir de https://reunido.uniovi.es/index.php/PST/article/view/19372

Resumen

Antecedentes: El diseño de medidas repetidas es uno de los más usados en ciencias sociales y de la salud. Aunque hay otras alternativas más avanzadas, el análisis de varianza de medidas repetidas (ANOVA-MR) sigue siendo el procedimiento más empleado para analizar las diferencias de medias. El impacto de la violación de la normalidad ha sido muy estudiado en el ANOVA intersujeto, pero los estudios son muy escasos en el ANOVA-MR. Por ello, el objetivo de este trabajo es realizar dos estudios de simulación Monte Carlo para analizar el error de Tipo I y la potencia cuando se incumple este supuesto bajo el cumplimiento de la esfericidad. Método: El estudio 1 incluye 20 distribuciones, tanto conocidas como desconocidas, manipulando el número de medidas repetidas (3, 4, 6 y 8) y el tamaño muestral (de 10 a 300). El estudio 2 incluye diferentes distribuciones en cada medida repetida. Las distribuciones analizadas representan desviación leve, moderada y severa de la normalidad. Resultados: En general, los resultados muestran que tanto el error Tipo I como la potencia del estadístico F no se alteran con la violación de la normalidad. Conclusiones: El ANOVA-MR es generalmente robusto a la no normalidad cuando la esfericidad se satisface.

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