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Does Kruskal-Wallis assume homogeneity of variance?
Kruskal-Wallis is used when researchers are comparing three or more independent groups on a continuous outcome, but the assumption of homogeneity of variance between the groups is violated in the ANOVA analysis. However, the statistical assumption of homogeneity of variance has been not met.
Is repeated measures ANOVA Parametric?
It is analagous to Repeated Measures ANOVA, but with the advantage of being non-parametric, and not requiring the assumptions of normality or homogeneity of variances. However, it has the limitation that it can only test a single explanatory variable at a time.
What is the difference between one-way Anova and Kruskal-Wallis test?
Hi! The dicision of using an ANOVA or Kruskal-Wallis test is the distribution of data. Normal / gaussian distribution should be analysed with ANOVA while a non-normal / non-gaussian distribution should be analysed with the Kruskal-Wallis. If nothing works, go ahead with the non-parametric test (Kruskal-Wallis).
Are there differences in the assumptions of Kruskal Wallis?
Are there differences in the assumptions? Kruskal-Wallis’ test is a non parametric one way anova. While Friedman’s test can be thought of as a (non parametric) repeated measure one way anova. If you don’t understand the difference, I compiled a list of tutorials I found about doing repeated measure anova with R, you can find them here
Which is less sensitive to outliers ANOVA or Kruskal Wallis?
The Kruskal-Wallis test does not assume normality in the data and is much less sensitive to outliers than the one-way ANOVA. Here are a couple examples of when you might conduct a Kruskal-Wallis test:
Is the Kruskal Wallis test compatible with parametric analysis?
If you use a parametric analysis as an alternative to the Kruskal-Wallis test, you should verify that your data meets the data requirements of that analysis. The data requirements for parametric analyses are not always compatible with the requirements for nonparametric analyses, such as the Kruskal-Wallis test.
Is the Kruskal Wallis H test an omnibus statistic?
It is important to realize that the Kruskal-Wallis H test is an omnibus test statistic and cannot tell you which specific groups of your independent variable are statistically significantly different from each other; it only tells you that at least two groups were different.