p_kruskal.test {Spower} | R Documentation |
p-value from Kruskal-Wallis Rank Sum Test simulation
Description
Simulates data given two or more parent distributions and
returns a p-value using kruskal.test
. Default generates data
from Gaussian distributions, however this can be modified.
Usage
p_kruskal.test(
n,
k,
means,
n.ratios = rep(1, k),
gen_fun = gen_kruskal.test,
...
)
gen_kruskal.test(n, k, n.ratios, means, ...)
Arguments
n |
sample size per group |
k |
number of groups |
means |
vector of means to control location parameters |
n.ratios |
allocation ratios reflecting the sample size ratios. Default of 1 sets the groups to be the same size (n * n.ratio) |
gen_fun |
function used to generate the required data.
Object returned must be a |
... |
additional arguments to pass to |
Value
a single p-value
Author(s)
Phil Chalmers rphilip.chalmers@gmail.com
Examples
# three group test where data generate from Gaussian distributions
p_kruskal.test(n=30, k=3, means=c(0, .5, .6))
# generate data from chi-squared distributions with different variances
gen_chisq <- function(n, k, n.ratios, means, dfs, ...){
dat <- vector('list', k)
ns <- n * n.ratios
for(g in 1:k)
dat[[g]] <- rchisq(ns[g], df=dfs[g]) - dfs[g] + means[g]
dat
}
p_kruskal.test(n=30, k=3, means=c(0, 1, 2),
gen_fun=gen_chisq, dfs=c(10, 15, 20))
# empirical power estimate
p_kruskal.test(n=30, k=3, means=c(0, .5, .6)) |> Spower()
p_kruskal.test(n=30, k=3, means=c(0, 1, 2), gen_fun=gen_chisq,
dfs = c(10, 15, 20)) |> Spower()
[Package Spower version 0.3.1 Index]