Test that two groups have the same population median
Compute the Kruskal-Wallis H-test for pairwise independent samples, from a given reference sample.
The Kruskal-Wallis H-test tests the null hypothesis that the population median of all of the groups are equal. It is a non-parametric version of ANOVA.
Input: a table containing the sample measurements, with the name of the samples.
Output: a table listing the Kruskal-Wallis H statistic, corrected for ties, and the p-value for each pairwise comparison testing. Kruskal-Wallis H statistic is corrected for ties. The p-value for the test uses the assumption that H has a chi square distribution. The p-value returned is the survival function of the chi square distribution evaluated at H.
for the test using the assumption that H has a chi square distribution. The p-value returned is the survival function of the chi square distribution evaluated at H.
- Config Parameters:
- "column_names": The columns used for pairwise comparison. By default, the first three columns are used.
Note: due to the assumption that H has a chi square distribution, the number of samples in each group must not be too small. A typical rule is that each sample must have at least 5 measurements.
For more details, see https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.kruskal.html
The names of column to pre-select for comparison. By default, the first 500 columns are used
The name of the column(s) to pre-select
Set True if it is a text pattern (regular expression), False otherwise
The column used as reference for pairwise comparison. Only this column is compared with the others.
The key of the row tag (representing the group axis) along which one would like to compare each column. This parameter is not used if a `reference column` is given.
Adjust p-values for multiple tests.
The method used to adjust (correct) p-values
FWER, family-wise error rate. Default is 0.05