pval {CIPerm}

Permutations-methods p-values for difference in means, medians, or Wilcoxon rank sum test

Description

Calculate p-values for a two-sample permutation or randomization test. In other words, we set up a permutation or randomization test to evaluate the null hypothesis that groups A and B have the same distribution, then calculate p-values for several alternatives: a difference in means (value="m"), a difference in medians (value="d"), or the Wilcoxon rank sum test (value="w").

Usage

pval(
  dset,
  tail = c("Two", "Left", "Right"),
  value = c("m", "s", "d", "w", "a")
)

Arguments

dset

The output of dset.

tail

Which tail? Either "Two"- or "Left"- or "Right"-tailed test.

value

Either "m" for difference in means (default); "s" for sum of Group 1 values [equivalent to "m" and included only for sake of checking results against Nguyen (2009) and Ernst (2004)]; "d" for difference in medians; or "w" for Wilcoxon rank sum statistic; or "a" for a named vector of all four p-values.

Value

Numeric p-value for the selected type of test, or a named vector of all four p-values if value="a".

Examples

x <- c(19, 22, 25, 26)
y <- c(23, 33, 40)
demo <- dset(x, y)
pval(dset = demo, tail = "Left", value = "s")
pval(dset = demo, tail = "Left", value = "a")