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While Bonferroni correction is a commonly used method for post hoc testing following a Kruskal-Wallis test, alternative approaches such as Dunn's test or the Conover-Iman test may also be employed. When selecting a post hoc test, researchers should consider factors such as the distribution of data, sample size, and the desired balance between Type I and Type II errors. Dunn's test is suitable for non-parametric data and provides greater power than Bonferroni correction, while the Conover-Iman test offers robustness against unequal sample sizes. It's important to assess the assumptions and requirements of each post hoc test and choose the most appropriate method based on the specific characteristics of the dataset and research question.