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While mixed model ANOVA and Aligned Ranked Sum serve different purposes and have distinct assumptions, normalizing the data and employing mixed model ANOVA may offer a viable alternative in certain scenarios. Mixed model ANOVA allows for the analysis of repeated measures or nested data structures and can accommodate both parametric and non-parametric data sets. By appropriately transforming and normalizing the data, researchers can mitigate violations of ANOVA assumptions and obtain robust statistical results. However, it's essential to consider the specific research context, data characteristics, and analytical objectives when selecting the appropriate statistical method, consulting with a statistician if necessary to ensure the chosen approach aligns with the study's requirements.