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p-value from Wilcoxon (signed rank) test simulation

Source: R/p_wilcox.test.R
p_wilcox.test.Rd

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,
  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?

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

Phil Chalmers rphilip.chalmers@gmail.com

Examples


# with normal distributions defaults d is standardized
p_wilcox.test(100, .5)
#> [1] 0.01026477
p_wilcox.test(100, .5, type = 'paired')  # n = number of pairs
#> [1] 2.590231e-05
p_wilcox.test(100, .5, type = 'one.sample')
#> [1] 8.892818e-09

# return analysis object
p_wilcox.test(100, .5, return_analysis = TRUE)
#> 
#> 	Wilcoxon rank sum test with continuity correction
#> 
#> data:  dat1 and dat2
#> W = 6235, p-value = 0.002558
#> alternative hypothesis: true location shift is not equal to 0
#> 

# 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)
#> [1] 0.8946873
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))
#> [1] 7.587524e-05