Kruskal-Wallis-test in R - ALL IN ONE (Calculation, Interpretation, Reporting)

// Kruskal-Wallis-test in R - ALL IN ONE (Calculation, Interpretation, Reporting) //

This video will help you in conducting a Kruskal-Wallis-test in R, including the calculation of post-hoc-tests, the effect size as well as interpreting and reporting its results.

Please don't forget that an a priori sample size calculation is usually required.

Calculating the required sample size:
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🎥    • Kruskal-Wallis-Test - calculate requi...  


The video consists of the following five parts:
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1) Calculation of the Kruskal-Wallis-test in R using the kruskal.test()-function.

2) Conducting post-hoc-tests to see which pairwise comparisons show differences worth investigating further (Dunn's tests are being used since they perform better with ties, compared to Mann-Whitney-Wilcoxon-tests).

3) Interpretation of the results, especially the post-hoc-tests.

4) Calculation of the effect size for the psot-hoc-tests of the Kruskal-Wallis-test, namely the effect size r. (Effect size Eta² for the Kruskal-Wallis-test is shown here:    • Effect size Eta-Squared for the Krusk...  )

5) Reporting of the results. Be aware that research field-specific standards may apply. The reporting shown is usually sufficient.


General information on the Kruskal-Wallis-test
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The Kruskal-Wallis-test is a non-parametric statistical method that is used in place of the one-way ANOVA when the data is not normally distributed. This test is used to assess whether the median of at least three groups is different. You can use a dependent variable that is at least on the ordinal scale.


📚 Sources:
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- Hoenig, J. M., & Heisey, D. M. (2001). The abuse of power: the pervasive fallacy of power calculations for data analysis. The American Statistician, 55(1), 19-24.
- Lantz, B. (2013). The large sample size fallacy. Scandinavian journal of caring sciences, 27(2), 487-492.
- Wasserstein, R. L., & Lazar, N. A. (2016). The ASA statement on p-values: context, process, and purpose. The American Statistician, 70(2), 129-133.


⏰ Timestamps:
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0:00 Introduction
0:15 0. Example
0:34 I. Requirements for the Kruskal-Wallis-test
0:42 II. Calculation and interpretation of the Kruskal-Wallis-test in R
1:57 III. Post-Hoc-Testing for the the Kruskal-Wallis-test in R
4:16 IV. Effect size for post-hoc-tests in R
5:25 Reporting the results


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