Nonparametric Tests of Group Differences in R

R provides functions for carrying out Mann-Whitney U, Wilcoxon Signed Rank, Kruskal Wallis, and Friedman tests.

# independent 2-group Mann-Whitney U Test
wilcox.test(y~A)
# where y is numeric and A is A binary factorDrivs av

# independent 2-group Mann-Whitney U Test
wilcox.test(y,x) # where y and x are numericDrivs av

# dependent 2-group Wilcoxon Signed Rank Test
wilcox.test(y1,y2,paired=TRUE) # where y1 and y2 are numericDrivs av

# Kruskal Wallis Test One Way Anova by Ranks
kruskal.test(y~A) # where y1 is numeric and A is a factorDrivs av

# Randomized Block Design - Friedman Test
friedman.test(y~A|B)
# where y are the data values, A is a grouping factor
# and B is a blocking factorDrivs av

For the wilcox.test you can use the alternative="less" or alternative="greater" option to specify a one tailed test.

Parametric and resampling alternatives are available.

The package pgirmess provides nonparametric multiple comparisons. (Note: This package has been withdrawn but is still available in the CRAN archives.)

library(npmc)
npmc(x)
#
where x is a data frame containing variable 'var'
#
(response variable) and 'class' (grouping variable)Drivs av

Visualizing Results

Use box plots or density plots to visual group differences.

To Practice

This interactive example allows you to practice the Wilcoxon Signed Rank test with R.