dunn_test {rstatix}

Dunn's Test of Multiple Comparisons

Description

Performs Dunn's test for pairwise multiple comparisons of the ranked data. The mean rank of the different groups is compared. Used for post-hoc test following Kruskal-Wallis test.

The default of the rstatix::dunn_test() function is to perform a two-sided Dunn test like the well known commercial softwares, such as SPSS and GraphPad. This is not the case for some other R packages (dunn.test and jamovi), where the default is to perform one-sided test. This discrepancy is documented at https://github.com/kassambara/rstatix/issues/50.

Usage

dunn_test(data, formula, p.adjust.method = "holm", detailed = FALSE)

Arguments

data

a data.frame containing the variables in the formula.

formula

a formula of the form x ~ group where x is a numeric variable giving the data values and group is a factor with one or multiple levels giving the corresponding groups. For example, formula = TP53 ~ cancer_group.

p.adjust.method

method to adjust p values for multiple comparisons. Used when pairwise comparisons are performed. Allowed values include "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none". If you don't want to adjust the p value (not recommended), use p.adjust.method = "none".

detailed

logical value. Default is FALSE. If TRUE, a detailed result is shown.

Details

DunnTest performs the post hoc pairwise multiple comparisons procedure appropriate to follow up a Kruskal-Wallis test, which is a non-parametric analog of the one-way ANOVA. The Wilcoxon rank sum test, itself a non-parametric analog of the unpaired t-test, is possibly intuitive, but inappropriate as a post hoc pairwise test, because (1) it fails to retain the dependent ranking that produced the Kruskal-Wallis test statistic, and (2) it does not incorporate the pooled variance estimate implied by the null hypothesis of the Kruskal-Wallis test.

Value

return a data frame with some of the following columns:

• .y.: the y (outcome) variable used in the test.

• group1,group2: the compared groups in the pairwise tests.

• n1,n2: Sample counts.

• estimate: mean ranks difference.

• estimate1, estimate2: show the mean rank values of the two groups, respectively.

• statistic: Test statistic (z-value) used to compute the p-value.

• p: p-value.

• p.adj: the adjusted p-value.

• method: the statistical test used to compare groups.

• p.signif, p.adj.signif: the significance level of p-values and adjusted p-values, respectively.

The returned object has an attribute called args, which is a list holding the test arguments.

References

Dunn, O. J. (1964) Multiple comparisons using rank sums Technometrics, 6(3):241-252.

Examples

# Simple test
ToothGrowth %>% dunn_test(len ~ dose)

# Grouped data
ToothGrowth %>%
  group_by(supp) %>%
  dunn_test(len ~ dose)