AB_permutation_test: AB_permutation_test

In pdt: Permutation Distancing Test

AB_permutation_test

Description

Performs a regular permutations test for two conditions or phases (A and B).

Usage

AB_permutation_test(
  x,
  y,
  test_statistic = "*",
  test_statistic_function = "mean",
  reps_max = 2000,
  no_duplicates = FALSE,
  show_plot = FALSE,
  show_plot_header = ""
)

Arguments

x	factor vector to indicate conditions or phases (e.g., "A" and "B")
y	numerical vector with the observed y-values
test_statistic	character how to compute the test statistic c("A-B", "B-A", "*") *=two-sided
test_statistic_function	character compute and compare "mean" or "median" for A and B
reps_max	numerical maximum number of permutation replications (the theoretical number= n!)
no_duplicates	boolean do a permutation test without duplicates (makes it much slower)
show_plot	boolean show test plot of statistical test
show_plot_header	character header of test plot

Value

List with the permutation test results: observed_test_statistic = computed test statistic, effect_size = computed effect size (similar to Cohen's d), random_assignments, p_randomization_AB = p value randomization AB test, one_sided_p = one-sided p-value in case of B-A or A-B.

Examples

pdt::AB_permutation_test(
  as.factor(c(rep("A",20), rep("B",20))),
  c(rnorm(20), rnorm(20)+2),
  test_statistic="B-A",
  test_statistic_function="mean",
  reps_max=1000,
  no_duplicates=FALSE,
  show_plot=FALSE,
  show_plot_header="")

pdt documentation built on Jan. 13, 2023, 1:13 a.m.