Add DOI from Zenodo

README.Rmd

@@ -20,6 +20,7 @@ knitr::opts_chunk$set(
 [![R-CMD-check](https://github.com/NeuroShepherd/ordinalsimr/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/NeuroShepherd/ordinalsimr/actions/workflows/R-CMD-check.yaml)
 [![CRAN status](https://www.r-pkg.org/badges/version/ordinalsimr)](https://CRAN.R-project.org/package=ordinalsimr)
 [![Codecov test coverage](https://codecov.io/gh/NeuroShepherd/ordinalsimr/branch/master/graph/badge.svg)](https://app.codecov.io/gh/NeuroShepherd/ordinalsimr?branch=master)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.14697216.svg)](https://doi.org/10.5281/zenodo.14697216)
 <!-- badges: end -->
 
 The {ordinalsimr} package assists in constructing simulation studies of ordinal data comparing two groups. It is intended to facilitate translation of methodological advances into practical settings for e.g. applied statisticians and data analysts who want to determine an appropriate statistical test to apply on their data or a proposed distribution of data.

README.md

@@ -12,6 +12,7 @@ experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](h
 status](https://www.r-pkg.org/badges/version/ordinalsimr)](https://CRAN.R-project.org/package=ordinalsimr)
 [![Codecov test
 coverage](https://codecov.io/gh/NeuroShepherd/ordinalsimr/branch/master/graph/badge.svg)](https://app.codecov.io/gh/NeuroShepherd/ordinalsimr?branch=master)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.14697216.svg)](https://doi.org/10.5281/zenodo.14697216)
 <!-- badges: end -->
 
 The {ordinalsimr} package assists in constructing simulation studies of

inst/CITATION

@@ -18,7 +18,8 @@ bibentry(
   urldate = "2025-01-19",
   copyright = "MIT",
   date = "2025-01",
-  abstract = "Simultaneously evaluate multiple ordinal outcome measures. Applied data analysts in particular are faced with uncertainty in choosing appropriate statistical tests for ordinal data. The included Shiny applications allows users to simulate outcomes given different ordinal data distributions."
+  abstract = "Simultaneously evaluate multiple ordinal outcome measures. Applied data analysts in particular are faced with uncertainty in choosing appropriate statistical tests for ordinal data. The included Shiny applications allows users to simulate outcomes given different ordinal data distributions.",
+  doi = 10.5281/zenodo.14697216
 )