Package: permutest 1.0.0

Amanda Glazer

permutest: Run Permutation Tests and Construct Associated Confidence Intervals

Implements permutation tests for any test statistic and randomization scheme and constructs associated confidence intervals as described in Glazer and Stark (2024) <doi:10.48550/arXiv.2405.05238>.

Authors:Amanda Glazer [aut, cre]

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# Install 'permutest' in R:
install.packages('permutest', repos = 'https://cloud.r-project.org')

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 155 downloads 17 exports 0 dependencies

Last updated 6 months agofrom:e065e46e35. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 26 2025
R-4.5-linuxOKMar 26 2025
R-4.4-linuxOKMar 26 2025

Exports:adjust_p_valuediff_in_meansdiff_in_mediansfisherliptaknpcone_sampleone_sample_meanone_way_anova_statpermutation_testpermutation_test_cipermute_grouppermute_signstrat_permute_grouptippettttest_stattwo_sample

Dependencies:

Citation

To cite package ‘permutest’ in publications use:

Glazer A (2024). permutest: Run Permutation Tests and Construct Associated Confidence Intervals. R package version 1.0.0, https://CRAN.R-project.org/package=permutest.

Corresponding BibTeX entry: 

  @Manual{,
    title = {permutest: Run Permutation Tests and Construct Associated
      Confidence Intervals},
    author = {Amanda Glazer},
    year = {2024},
    note = {R package version 1.0.0},
    url = {https://CRAN.R-project.org/package=permutest},
  }

Readme and manuals

permutest

The goal of permutest is to allow users to run permutation tests and construct associated confidence intervals for any test statistic and any set of permutations.

Installation

You can install the development version of permutest from GitHub with:

# install.packages("devtools")
devtools::install_github("akglazer/permutest")

Example

This is a basic example which shows you how to use the permutation test function with a difference in means test statistic:

library(permutest)

data <- data.frame(group = c(rep(1, 10), rep(2, 10)),
                     outcome = c(rep(1, 10), rep(1, 10)))

output <- permutation_test(df = data, group_col = "group", outcome_col = "outcome",
                   test_stat = "diff_in_means", perm_func = permute_group,
                   alternative = "greater", shift = 0, reps = 10,
                   return_perm_dist = F, return_test_dist = T, seed = 42)

Alternatively, for the two-sample problem with difference in means test statistic, you can use the function two_sample() (and for the one-sample problem you can use one_sample()):

output <- two_sample(x = c(10, 9, 11), y = c(12, 11, 13), alternative = "less", seed = 42)

The following is an example of how to construct a confidence interval for a shift parameter in the two-sample problem:

x <- c(35.3, 35.9, 37.2, 33.0, 31.9, 33.7, 36.0, 35.0,
         33.3, 33.6, 37.9, 35.6, 29.0, 33.7, 35.7)
y <- c(32.5, 34.0, 34.4, 31.8, 35.0, 34.6, 33.5, 33.6,
         31.5, 33.8, 34.6)
df <- data.frame(outcome = c(x, y), group = c(rep(1, length(x)), rep(0, length(y))))

output <- permutation_test_ci(df, "group", "outcome", strata_col = NULL,
                      test_stat = "diff_in_means",
                      perm_func = permute_group,
                      upper_bracket = NULL,
                      lower_bracket = NULL,
                      cl = 0.95,
                      e = 0.01,
                      reps = 100000,
                      seed = 42)