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Kruskal-Wallis test

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The Kruskal-Wallis test (H-test) is an extension of the Wilcoxon test and can be used to test the hypothesis that a number of unpaired samples originate from the same population. In MedCalc, Factor codes are used to break-up the (ordinal) data in one variable into different sample subgroups. If the null-hypothesis, being the hypothesis that the samples originate from the same population, is rejected (P<0.05), then the conclusion is that there is a statistically significant difference between at least two of the subgroups.

Required input

Dialog box for Kruskal-Wallis test

The following need to be entered in the dialog box: for Data select the variable containing the data, and for Factor codes the qualitative factor. The qualitative factor may either be character or numeric codes. These are the codes that will be used to break-up the data into several subgroups.



Kruskal-Wallis test - results

In this example, it is tested whether different treatment regimens coded A, B and C in the variable Treatment, have an influence on the data in the variable Pain_relief. Pain relief was recorded on an ordinal scale from 0 to 9. Since the null-hypothesis is not rejected (P=0.1995), the conclusion is that there is no statistical significant difference between the different treatments.

For a graphical representation of this test, refer to Multiple comparison graphs.

Post-hoc analysis

If the Kruskal-Wallis test is positive (P less than the selected significance level) then MedCalc performs a test for pairwise comparison of subgroups.


See also

External links

Recommended book

Book cover

Practical Nonparametric Statistics
W. J. Conover

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This classic text and reference book is intended mainly for one-semester advanced undergraduate and undergrad/graduate introductory courses in nonparametric (or distribution free) statistics. The book will also appeal to applied research workers as a quick reference to the most useful nonparametric methods.