kwsamplesize function

Sample Size for the Kruskal-Wallis test.

kwsamplesize approximates sample 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.

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

Arguments

• shifts: The offsets for the various populations, under the alternative hypothesis.
• 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.
• taylor: Logical flag forcing the approximation of exceedence probabilities using the first derivative at zero.

Returns

A list with the total number of observations needed to obtain approximate power, as long as this number is split amomg groups according to argument proportion.

Details

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

Examples

#Calculate the sample size necessary to detect differences among three
#groups with centers at 0,1,2, from normal observations, using a test of
#level 0.05 and power 0.80.
kwsamplesize(c(0,1,2),"normal")