{"id":21625723,"url":"https://github.com/dcousin3/anofa","last_synced_at":"2026-02-07T07:34:06.147Z","repository":{"id":207233746,"uuid":"718753027","full_name":"dcousin3/ANOFA","owner":"dcousin3","description":"Analysis of Frequency Data with ANOFA","archived":false,"fork":false,"pushed_at":"2025-01-05T20:01:34.000Z","size":2072,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-12-09T12:59:18.944Z","etag":null,"topics":["frequencies","r","statistics"],"latest_commit_sha":null,"homepage":"https://dcousin3.github.io/ANOFA","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/dcousin3.png","metadata":{"files":{"readme":"README.Rmd","changelog":"NEWS.md","contributing":null,"funding":null,"license":null,"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,"zenodo":null}},"created_at":"2023-11-14T18:21:23.000Z","updated_at":"2025-01-05T20:01:38.000Z","dependencies_parsed_at":"2023-11-16T23:55:26.979Z","dependency_job_id":"5b0f0d78-05cf-4db5-9988-6f1400145edf","html_url":"https://github.com/dcousin3/ANOFA","commit_stats":null,"previous_names":["dcousin3/anofa"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/dcousin3/ANOFA","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dcousin3%2FANOFA","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dcousin3%2FANOFA/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dcousin3%2FANOFA/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dcousin3%2FANOFA/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/dcousin3","download_url":"https://codeload.github.com/dcousin3/ANOFA/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dcousin3%2FANOFA/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29189375,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-07T05:07:31.176Z","status":"ssl_error","status_checked_at":"2026-02-07T05:06:15.227Z","response_time":63,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["frequencies","r","statistics"],"created_at":"2024-11-25T01:10:24.441Z","updated_at":"2026-02-07T07:34:06.130Z","avatar_url":"https://github.com/dcousin3.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"---\noutput: github_document\nbibliography: \"inst/REFERENCES.bib\"\ncsl: \"inst/apa-6th.csl\"\n---\n\n# ANOFA: Analyses of Frequency Data\n\n\u003c!-- badges: start --\u003e\n[![CRAN Status](https://www.r-pkg.org/badges/version/ANOFA)](https://cran.r-project.org/package=ANOFA)\n\u003c!-- badges: end --\u003e\n\n```{r, echo = FALSE, message = FALSE, results = 'hide', warning = FALSE}\ncat(\"this will be hidden; used for general initializations.\\n\")\nlibrary(ANOFA)\noptions(\"ANOFA.feedback\" = \"none\") # shut down all information\n```\n\nThe library `ANOFA` provides easy-to-use tools to analyze frequency data. \nIt does so using the _Analysis of Frequency datA_ (ANOFA) framework \n[the full reference @lc23b]. With this set of tools, you can examined\nif classification factors are non-equal (_have an effect_) and if their\ninteractions (in case you have more than 1 factor) are significant. You\ncan also examine simple effects (a.k.a. _expected marginal_ analyses). \nFinally, you can assess differences based on orthogonal contrasts.\nANOFA also comes with tools to make a plot of the frequencies along\nwith 95% confidence intervals [these intervals are adjusted for pair-\nwise comparisons @cgh21]; with tools to compute statistical power given\nsome _a priori_ expected frequencies or sample size to reach a certain\nstatistical power. In sum, eveything you need to analyse frequencies!\n\nThe main function is `anofa()` which provide an omnibus analysis of the \nfrequencies for the factors given. For example, @lm71 explore frequencies\nfor attending a certain type of higher education as a function of gender:\n\n```{r, message=FALSE, warning=FALSE, echo=TRUE, eval=TRUE}\nw \u003c- anofa( obsfreq ~ vocation * gender, LightMargolin1971)\nsummary(w)\n```\n\nA plot of the frequencies can be obtained easily with \n\n```{r, message=FALSE, warning=FALSE}\nanofaPlot(w) \n```\n\nOwing to the interaction, simple effects can be analyzed from the _expected marginal\nfrequencies_ with\n\n```{r, message=FALSE, warning=FALSE, echo=TRUE, eval=TRUE}\ne \u003c- emFrequencies(w, ~ gender | vocation )\nsummary(e)\n```\n\nFollow-up functions includes contrasts examinations with `contrastFrequencies()'.\n\nPower planning can be performed on frequencies using ``anofaPower2N()`` or\n``anofaN2Power()`` if you can determine theoretical frequencies.\n\nFinally, `toRaw()`, `toCompiled()`, `toTabular()`, `toLong()` and `toWide()` \ncan be used to present the frequency data in other formats.\n\n# Installation\n\nNote that the package is named using UPPERCASE letters whereas the main function is in lowercase letters.\n\nThe official **CRAN** version can be installed with \n\n```{r, echo = TRUE, eval = FALSE}\ninstall.packages(\"ANOFA\")\nlibrary(ANOFA)\n```\n\nThe development version `r packageVersion(\"ANOFA\")` can be accessed through GitHub:\n\n```{r, echo = TRUE, eval = FALSE}\ndevtools::install_github(\"dcousin3/ANOFA\")\nlibrary(ANOFA)\n```\n\nThe library is loaded with \n\n```{r, echo = TRUE, eval = FALSE, results = FALSE}\nlibrary(ANOFA)\n```\n\n# For more\n\nAs seen, the library `ANOFA` makes it easy to analyze frequency data.\nIts general philosophy is that of ANOFAs.\n\nThe complete documentation is available on this \n[site](https://dcousin3.github.io/ANOFA/).\n\nA general introduction to the `ANOFA` framework underlying this \nlibrary can be found at *the Quantitative Methods for Psychology* @lc23b.\n\n# References\n\n\\insertAllCited{}\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdcousin3%2Fanofa","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdcousin3%2Fanofa","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdcousin3%2Fanofa/lists"}