AB_permutation_test {pdt} | R Documentation |
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="")