{"id":24906203,"url":"https://github.com/mightymetrika/npboottprm","last_synced_at":"2025-03-27T22:22:25.457Z","repository":{"id":184878216,"uuid":"672618477","full_name":"mightymetrika/npboottprm","owner":"mightymetrika","description":"Nonparametric Bootstrap Test with Pooled Resampling","archived":false,"fork":false,"pushed_at":"2024-02-24T15:18:25.000Z","size":221,"stargazers_count":0,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2024-04-26T09:04:23.631Z","etag":null,"topics":["datascience","nonparametric","r","statistics"],"latest_commit_sha":null,"homepage":"","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/mightymetrika.png","metadata":{"files":{"readme":"README.Rmd","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-07-30T17:33:47.000Z","updated_at":"2024-06-16T18:09:10.694Z","dependencies_parsed_at":"2023-11-17T18:30:36.743Z","dependency_job_id":"fdc28e68-f9da-4dac-a452-d15701dfa065","html_url":"https://github.com/mightymetrika/npboottprm","commit_stats":{"total_commits":36,"total_committers":2,"mean_commits":18.0,"dds":0.3055555555555556,"last_synced_commit":"3491f612c1091b43040eb02153254eb941c6444d"},"previous_names":["mightymetrika/npboottprm"],"tags_count":3,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mightymetrika%2Fnpboottprm","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mightymetrika%2Fnpboottprm/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mightymetrika%2Fnpboottprm/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mightymetrika%2Fnpboottprm/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mightymetrika","download_url":"https://codeload.github.com/mightymetrika/npboottprm/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245932332,"owners_count":20696038,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["datascience","nonparametric","r","statistics"],"created_at":"2025-02-02T00:39:08.613Z","updated_at":"2025-03-27T22:22:25.410Z","avatar_url":"https://github.com/mightymetrika.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"---\noutput: github_document\n---\n\n\u003c!-- README.md is generated from README.Rmd. Please edit that file --\u003e\n\n```{r, include = FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"man/figures/README-\",\n  out.width = \"100%\"\n)\n```\n\n# npboottprm\n\n\u003c!-- badges: start --\u003e\n\u003c!-- badges: end --\u003e\n\nThe goal of npboottprm is to provide a robust tool for conducting nonparametric bootstrap tests with pooled resampling. These tests are ideal for small sample sizes and include the independent t-test, paired t-test, and F-test. The package employs methods presented in Dwivedi, Mallawaarachchi, and Alvarado (2017). \n\n## Installation\n\nYou can install the released version of npboottprm from [CRAN](https://CRAN.R-project.org):\n\n```{r eval=FALSE}\ninstall.packages(\"npboottprm\")\n```\n\n\nTo install the development version of npboottprm from GitHub, use the [devtools](https://devtools.r-lib.org/) package:\n\n```{r, eval=FALSE}\n# install.packages(\"devtools\")\ndevtools::install_github(\"mightymetrika/npboottprm\")\n```\n\n\n## Nonparametric bootstrap t-test\n\nThe following example demonstrates how to use the nonparboot() function to conduct an independent t-test.\n\n```{r}\nlibrary(npboottprm)\n\n# Use the simulated data included in the package\nprint(data_t)\n\n# Run the test\nres_t \u003c- nonparboot(data = data_t,\n                    x = \"x\",\n                    grp = \"grp\",\n                    nboot = 1000,\n                    test = \"t\",\n                    conf.level = 0.95,\n                    seed = 183)\n\n# Print the results, excluding the bootstrap distributions\nprint(res_t[!names(res_t) %in%\n              c(\"bootstrap.stat.dist\", \"bootstrap.effect.dist\")])\n```\n\n\n## Nonparametric bootstrap paired t-test\n\nThe following example demonstrates how to use the nonparboot() function to conduct a paired t-test.\n\n```{r}\n# Use the simulated data included in the package\nprint(data_pt)\n\n# Run the test\nres_pt \u003c- nonparboot(data = data_pt,\n                     x = \"x\",\n                     y = \"y\",\n                     nboot = 1000,\n                     test = \"pt\",\n                     conf.level = 0.95,\n                     seed = 166)\n\n# Print the results, excluding the bootstrap distributions\nprint(res_pt[!names(res_pt) %in%\n               c(\"bootstrap.stat.dist\", \"bootstrap.effect.dist\")])\n```\n\n\n## Nonparametric bootstrap F-test\n\nThe following example demonstrates how to use the nonparboot() function to conduct an F-test.\n\n```{r}\n# Use the simulated data included in the package\nprint(data_f)\n\n# Run the test\nres_f \u003c- nonparboot(data = data_f,\n                    x = \"x\",\n                    grp = \"grp\",\n                    nboot = 1000,\n                    test = \"F\",\n                    conf.level = 0.95,\n                    seed = 397)\n\n# Print the results, excluding the bootstrap distributions\nprint(res_f[!names(res_f) %in%\n              c(\"bootstrap.stat.dist\", \"bootstrap.effect.dist\")])\n```\n\n\nPlease note that the examples provided here use simulated data included in the package. When using this package with your own data, replace data_t, data_pt, and data_f with your own data frames, and adjust the x, y, and grp parameters as needed.\n\n## References\n\nDwivedi AK, Mallawaarachchi I, Alvarado LA (2017). \"Analysis of small sample size studies using nonparametric bootstrap test with pooled resampling method.\" Statistics in Medicine, 36 (14), 2187-2205.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmightymetrika%2Fnpboottprm","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmightymetrika%2Fnpboottprm","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmightymetrika%2Fnpboottprm/lists"}