kweffectsize approximates effect size for the Kruskal-Wallis test,
using a chi-square approximation under the null, and a non-central chi-square approximation under the alternative. The noncentrality parameter is calculated using alternative means and the null variance structure.
kweffectsize(
totsamp,
shifts,
distname = c("normal", "logistic"),
targetpower = 0.8,
proportions = rep(1, length(shifts))/length(shifts),
level = 0.05
)A list with components power, giving the power approximation, ncp, giving the noncentrality parameter, cv, giving the critical value, probs, giving the intermediate output from pairwiseprobability, and expect, the quantities summed before squaring in the noncentrality parameter.
sample size
The offsets for the various populations, under the alternative hypothesis. This is used for direction on input.
The distribution of the underlying observations; normal and logistic are currently supported.
The distribution of the underlying observations; normal and logistic are currently supported.
The proportions in each group.
The test level.
The standard noncentral chi-square power formula, or Monte Carlo, is used.
kwpower(rep(10,3),c(0,1,2),"normal")
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