Here’s the code I used: kruskal.test(mean_severity~month, data= dat) Kruskal-Wallis rank sum test. data: mean_severity by month. Kruskal-Wallis chi-squared = 20.172, df = 7, p-value = 0.00521. The obtained p-value indicates a significant difference in disease severity among the months. To further analyze and visualize the differences, I used.. Caveat: there are a few less well-known post hoc pair-wise tests to follow a rejected Kruskal-Wallis, including Conover-Iman (like Dunn, but based on the t distribution, rather than the z distribution, and strictly more powerful as a post hoc test) which is implemented for Stata in the conovertest package (within Stata type net describe.
Results (p values) of the KruskalWallis with Bonferroni post hoc test
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Prueba de KRUSKAL WALLIS
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Prueba de KruskalWallis YouTube
A. Prueba Kruskal Wallis para comparar los halos de inhibición del
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A Kruskal-Wallis test requires 3 assumptions 1, 5, 8: independent observations; the dependent variable must be quantitative or ordinal; sufficient sample sizes (say, each n i ≥ 5) unless the exact significance level is computed. Regarding the last assumption, exact p-values for the Kruskal-Wallis test can be computed.. To perform a Kruskal-Wallis test in SPSS, click Analyze -> Nonparametric tests -> Independent Samples… as illustrated below: This brings up the Nonparametric Tests: Two or More Independent Samples dialog box. Select the Fields tab. Select your independent (or grouping) variable (e.g., Major), and use the arrow button to move it to the Groups box.