p_wilcox.test: p-value from Wilcoxon (signed rank) test simulation

In Spower: Power Analyses using Monte Carlo Simulations

p-value from Wilcoxon (signed rank) test simulation

Description

Simulates data given one (Wilcoxon) or two (Mann-Whitney) parent distributions and returns a p-value. Can also be used for power analyses related to sign tests.

Usage

p_wilcox.test(
  n,
  d,
  n2_n1 = 1,
  mu = 0,
  type = c("two.sample", "one.sample", "paired"),
  exact = NULL,
  correct = TRUE,
  two.tailed = TRUE,
  alternative = NULL,
  parent1 = function(n, d) rnorm(n, d, 1),
  parent2 = function(n, d) rnorm(n, 0, 1),
  return_analysis = FALSE
)

Arguments

n	sample size per group. For paired samples this corresponds to the number of pairings (hence, half of the data points observed)
d	effect size passed to parent functions
n2_n1	sample size ratio
mu	parameter used to form the null hypothesis
type	type of analysis to use (two-sample, one-sample, or paired)
exact	a logical indicating whether an exact p-value should be computed
correct	a logical indicating whether to apply continuity correction in the normal approximation for the p-value
two.tailed	logical; use two-tailed test? For one-tailed tests relevant alternative arguments are set to 'greater'
alternative	character vector passed to alternative analysis function (most commonly, 'two.tailed', 'greater', 'less'). When used, ignores the value of two.tailed
parent1	data generation function for first group. Ideally should have SDs = 1 so that d reflects a standardized difference
parent2	same as parent1, but for the second group
return_analysis	logical; return the analysis object for further extraction and customization?

Value

a single p-value

Author(s)

Phil Chalmers [e-mail]

Examples

# with normal distributions defaults d is standardized
p_wilcox.test(100, .5)
p_wilcox.test(100, .5, type = 'paired')  # n = number of pairs
p_wilcox.test(100, .5, type = 'one.sample')

# return analysis object
p_wilcox.test(100, .5, return_analysis = TRUE)

# using chi-squared distributions (standardizing to 0-1)
p_wilcox.test(100, .5, type = 'one.sample',
   parent1 = function(n, d) rchisq(n, df=10) - 10 + d)
p_wilcox.test(100, .5,
   parent1 = function(n, d) (rchisq(n, df=10) - 10)/sqrt(20) + d,
   parent2 = function(n, d) (rchisq(n, df=10) - 10)/sqrt(20))

Spower documentation built on Oct. 16, 2026, 9:08 a.m.