{"id":23508628,"url":"https://github.com/adelahladka/difnlr","last_synced_at":"2025-04-16T14:39:57.543Z","repository":{"id":56935353,"uuid":"73820988","full_name":"adelahladka/difNLR","owner":"adelahladka","description":"DIF and DDF Detection by Non-Linear Regression Models.","archived":false,"fork":false,"pushed_at":"2025-03-20T20:53:13.000Z","size":6446,"stargazers_count":6,"open_issues_count":2,"forks_count":3,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-29T05:23:29.216Z","etag":null,"topics":["differential-item-functioning","item-analysis","psychometrics","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":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/adelahladka.png","metadata":{"files":{"readme":"README.md","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}},"created_at":"2016-11-15T14:24:15.000Z","updated_at":"2025-03-20T20:53:17.000Z","dependencies_parsed_at":"2024-01-29T09:53:49.053Z","dependency_job_id":"798b8ba3-5522-40b2-a7ed-ad14de5e10a0","html_url":"https://github.com/adelahladka/difNLR","commit_stats":{"total_commits":204,"total_committers":3,"mean_commits":68.0,"dds":0.4117647058823529,"last_synced_commit":"3d46d03fbd73678bcff5f72f1792e9f76b987f29"},"previous_names":[],"tags_count":23,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adelahladka%2FdifNLR","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adelahladka%2FdifNLR/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adelahladka%2FdifNLR/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adelahladka%2FdifNLR/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/adelahladka","download_url":"https://codeload.github.com/adelahladka/difNLR/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":249250971,"owners_count":21237965,"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":["differential-item-functioning","item-analysis","psychometrics","r","statistics"],"created_at":"2024-12-25T11:24:37.662Z","updated_at":"2025-04-16T14:39:57.536Z","avatar_url":"https://github.com/adelahladka.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# difNLR\nDIF and DDF Detection by Non-Linear Regression Models.\n\n[![R-CMD-check](https://github.com/adelahladka/difNLR/workflows/R-CMD-check/badge.svg)](https://github.com/adelahladka/difNLR/actions)\n![GHversion](https://img.shields.io/github/release/adelahladka/difNLR.svg)\n[![version](https://www.r-pkg.org/badges/version/difNLR)](https://CRAN.R-project.org/package=difNLR)\n![cranlogs](https://cranlogs.r-pkg.org/badges/difNLR)\n\n## Description\nThe `difNLR` package provides methods for detecting differential item\nfunctioning (DIF) using non-linear regression models. Both uniform and\nnon-uniform DIF effects can be detected when considering a single focal group.\nAdditionally, the method allows for testing differences in guessing or\ninattention parameters between the reference and focal group. DIF detection is\nperformed using either a likelihood-ratio test, an F-test, or Wald's test of a\nsubmodel. The software offers a variety of algorithms for estimating item\nparameters.\n\nFurthermore, the `difNLR` package includes methods for detecting differential\ndistractor functioning (DDF) using multinomial log-linear regression model. It\nalso introduces DIF detection approaches for ordinal data via adjacent category\nlogit and cumulative logit regression models.\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"inst/DIF_NLR.png\" width=32%/\u003e \n  \u003cimg src=\"inst/DDF_CLRM_cumulative.png\" width=32%/\u003e \n  \u003cimg src=\"inst/DDF_CLRM_category.png\" width=32%/\u003e \n\u003c/p\u003e\n\n\n## Installation\nThe easiest way to get `difNLR` package is to install it from CRAN:\n```\ninstall.packages(\"difNLR\")\n```\nOr you can get the newest development version from GitHub:\n```\n# install.packages(\"devtools\")\ndevtools::install_github(\"adelahladka/difNLR\")\n```\n## Version\nCurrent version on [**CRAN**](https://CRAN.R-project.org/package=difNLR) is\n1.5.1-1. The newest development version available on\n[**GitHub**](https://github.com/adelahladka/difNLR) is 1.5.1-2.\n\n## Reference\nTo cite `difNLR` package in publications, please, use:\n\n\u003cul\u003eHladka, A. \u0026 Martinkova, P. (2020). difNLR: Generalized logistic regression models for DIF and DDF detection. \n  \u003ci\u003eThe R Journal, 12\u003c/i\u003e(1), 300--323, \n  https://doi.org/10.32614/RJ-2020-014\u003c/ul\u003e\n\n\u003cul\u003eDrabinova, A. \u0026 Martinkova, P. (2017). Detection of Differential Item Functioning with\n  Nonlinear Regression: A Non-IRT Approach Accounting for Guessing. \n  \u003ci\u003eJournal of Educational Measurement, 54\u003c/i\u003e(4), 498--517, \n  https://doi.org/10.1111/jedm.12158\u003c/ul\u003e\n  \n\nTo cite new estimation approaches provided in the `difNLR()` function, please, use:\n\n\u003cul\u003eHladka, A., Martinkova, P., \u0026 Brabec, M. (2024). New iterative algorithms for estimation of item functioning. \n  \u003ci\u003eJournal of Educational and Behavioral Statistics. \u003c/i\u003e \n  Online first, https://doi.org/10.3102/10769986241312354\u003c/ul\u003e\n  \n## Try online\nYou can try some functionalities of the `difNLR` package\n[online](https://shiny.cs.cas.cz/ShinyItemAnalysis/) using\n[`ShinyItemAnalysis`](https://github.com/patriciamar/ShinyItemAnalysis)\napplication and package and its DIF/Fairness section.\n  \n## Getting help\nIn case you find any bug or just need help with the `difNLR` package, you can leave\nyour message as an issue here or directly contact us at hladka@cs.cas.cz\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadelahladka%2Fdifnlr","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fadelahladka%2Fdifnlr","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadelahladka%2Fdifnlr/lists"}