kweffectsize: Sample Size for the Kruskal-Wallis test.

In MultNonParam: Multivariate Nonparametric Methods

Sample Size for the Kruskal-Wallis test.

Description

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.

Usage

kweffectsize(
  totsamp,
  shifts,
  distname = c("normal", "logistic", "cauchy"),
  targetpower = 0.8,
  proportions = rep(1, length(shifts))/length(shifts),
  level = 0.05
)

Arguments

totsamp	sample size
shifts	The offsets for the various populations, under the alternative hypothesis. This is used for direction on input.
distname	The distribution of the underlying observations; normal and logistic are currently supported.
targetpower	The distribution of the underlying observations; normal and logistic are currently supported.
proportions	The proportions in each group.
level	The test level.

Details

The standard noncentral chi-square power formula, or Monte Carlo, is used.

Value

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.

Examples

#Calculate the effecct size necessary to have the desired power .8 for a test
#with the level .5 with sample size 60, group centers 0, 1, and 2, 
#normally distributed observations, evenly split among the three groups.
kweffectsize(60,c(0,1,2),"normal")

MultNonParam documentation built on Aug. 30, 2023, 9:09 a.m.