kruskal_wallis_internal {pseudorank} | R Documentation |
Hettmansperger-Norton Trend Test for k-Samples
Description
This function calculates the Kruskal-Wallis test using pseudo-ranks under the null hypothesis H0F: F_1 = ... F_k.
Usage
kruskal_wallis_internal(
data,
group,
na.rm,
formula = NULL,
pseudoranks = TRUE,
...
)
Arguments
data |
numeric vector containing the data |
group |
factor specifying the groups |
na.rm |
a logical value indicating if NA values should be removed |
formula |
formula object |
pseudoranks |
logical value indicating if pseudo-ranks or ranks should be used |
... |
further arguments are ignored |
Value
Returns a data.frame with the results
References
Brunner, E., Bathke, A.C., and Konietschke, F. (2018a). Rank- and Pseudo-Rank Procedures for Independent Observations in Factorial Designs - Using R and SAS. Springer Series in Statistics, Springer, Heidelberg. ISBN: 978-3-030-02912-8.
Hettmansperger, T. P., & Norton, R. M. (1987). Tests for patterned alternatives in k-sample problems. Journal of the American Statistical Association, 82(397), 292-299
Examples
x = c(1, 1, 1, 1, 2, 3, 4, 5, 6)
grp = as.factor(c('A','A','B','B','B','D','D','D','D'))
# calculate Kruskal-Wallis test using pseudo-ranks
kruskal_wallis_test(x, grp, na.rm = FALSE, pseudoranks = TRUE)