hettmansperger_norton_test_internal {pseudorank} | R Documentation |
Hettmansperger-Norton Trend Test for k-Samples
Description
This function calculates the Hettmansperger-Norton trend test using pseudo-ranks under the null hypothesis H0F: F_1 = ... F_k.
Usage
hettmansperger_norton_test_internal(
data,
group,
na.rm,
alternative = c("decreasing", "increasing", "custom"),
formula = NULL,
trend = NULL,
pseudoranks = TRUE,
...
)
Arguments
data |
numeric vector containing the data |
group |
ordered factor vector for the groups |
na.rm |
a logical value indicating if NA values should be removed |
alternative |
either decreasing or increasing |
formula |
formula object |
trend |
custom numeric vector indicating the trend for the custom alternative, only used if alternative = "custom" |
... |
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
# create some data, please note that the group factor needs to be ordered
df <- data.frame(data = c(rnorm(40, 3, 1), rnorm(40, 2, 1), rnorm(20, 1, 1)),
group = c(rep(1,40),rep(2,40),rep(3,20)))
df$group <- factor(df$group, ordered = TRUE)
# you can either test for a decreasing, increasing or custom trend
hettmansperger_norton_test(df$data, df$group, alternative="decreasing")
hettmansperger_norton_test(df$data, df$group, alternative="increasing")
hettmansperger_norton_test(df$data, df$group, alternative="custom", trend = c(1, 3, 2))