{"id":23069557,"url":"https://github.com/tmsalab/edina","last_synced_at":"2025-08-15T13:32:17.068Z","repository":{"id":56936439,"uuid":"108773715","full_name":"tmsalab/edina","owner":"tmsalab","description":"Perform a Bayesian estimation of the Exploratory Deterministic Input, Noisy “And” Gate (EDINA) cognitive diagnostic model described by Chen et al. 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Please edit that file --\u003e\n\n```{r, echo = FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"README-\"\n)\n```\n\n# edina\n\n\u003c!-- badges: start --\u003e\n[![R build status](https://github.com/tmsalab/edina/workflows/R-CMD-check/badge.svg)](https://github.com/tmsalab/edina/actions)\n[![Package-License](http://img.shields.io/badge/license-GPL%20(%3E=2)-brightgreen.svg?style=flat)](http://www.gnu.org/licenses/gpl-2.0.html)\n[![CRAN Version Badge](http://www.r-pkg.org/badges/version/edina)](https://cran.r-project.org/package=edina)\n[![CRAN Status](https://cranchecks.info/badges/worst/edina)](https://cran.r-project.org/web/checks/check_results_edina.html)\n[![RStudio CRAN Mirror's Monthly Downloads](http://cranlogs.r-pkg.org/badges/edina?color=brightgreen)](http://www.r-pkg.org/pkg/edina)\n[![RStudio CRAN Mirror's Total Downloads](http://cranlogs.r-pkg.org/badges/grand-total/edina?color=brightgreen)](http://www.r-pkg.org/pkg/edina)\n\u003c!-- badges: end --\u003e\n\nPerform a Bayesian estimation of the Exploratory \nDeterministic Input, Noisy \"And\" Gate (EDINA)\ncognitive diagnostic model described by Chen et al. (2018).\n\n## Installation\n\nYou can install `edina` from CRAN using:\n\n```{r cran-installation, eval = FALSE}\ninstall.packages(\"edina\")\n```\n\nOr, you can be on the cutting-edge development version on GitHub using:\n\n```{r gh-installation, eval = FALSE}\nif(!requireNamespace(\"devtools\")) install.packages(\"devtools\")\ndevtools::install_github(\"tmsalab/edina\")\n```\n\n## Usage\n\nTo use the `edina` package, load it into _R_ using:\n\n```{r example, message = FALSE}\nlibrary(\"edina\")\n```\n\nFrom there, the EDINA model can be estimated using:\n\n```{r edina-est, eval = FALSE}\nedina_model = edina(\u003cdata\u003e, chain_length = 10000)\n```\n\nTo compute a model underneath different _K_ attribute configured _Q_ matrices, use:\n\n```{r edina-multiple, eval = FALSE}\nedina_model = auto_edina(\u003cdata\u003e, k = 2:4, chain_length = 10000)\n```\n\n**Note:** Higher _K_ configured _Q_ matrices take longer to estimate. \n\n## Authors\n\nJames Joseph Balamuta, Steven Andrew Culpepper, and Jeffrey A. Douglas\n\n## Citing the `edina` package\n\nTo ensure future development of the package, please cite `edina`\npackage if used during an analysis or simulation studies. Citation information\nfor the package may be acquired by using in *R*:\n\n```{r, eval = FALSE}\ncitation(\"edina\")\n```\n\n## License\n\nGPL (\u003e= 2)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftmsalab%2Fedina","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftmsalab%2Fedina","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftmsalab%2Fedina/lists"}