ordinalsimr

R package and Shiny app for simulating ordinal endpoint results. Try it here: https://6fcd1k-pat.shinyapps.io/ordinalsimr/

https://github.com/neuroshepherd/ordinalsimr

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 3 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (20.3%) to scientific vocabulary

Keywords

ordinal r shiny
Last synced: 6 months ago · JSON representation ·

Repository

R package and Shiny app for simulating ordinal endpoint results. Try it here: https://6fcd1k-pat.shinyapps.io/ordinalsimr/

Basic Info
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • Open Issues: 19
  • Releases: 8
Topics
ordinal r shiny
Created almost 3 years ago · Last pushed 7 months ago
Metadata Files
Readme Changelog License Citation

README.Rmd

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# ordinalsimr 


[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[![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.14697215.svg)](https://doi.org/10.5281/zenodo.14697215)



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.

This package is primarily developed as a Shiny application which abstracts away the heavier coding aspect of setting up simulation studies. Instead, users can simply enter parameters and data distributions into the application, and save the results as an `.rds` file. The structure of the Shiny application only allows for one simulation to be specified at a time as opposed to a grid of parameters. However, the underlying functions for running the simulations are accessible. See `vignette("ordinalsimr")` for template code on setting up your own simulations manually. 

## Installation

You can install the development version of ordinalsimr from GitHub with:

``` r
# install.packages("devtools")
devtools::install_github(
  "NeuroShepherd/ordinalsimr",
  build_vignettes = TRUE
)
```

## Running the App

The app can be started with the following code:

``` r
ordinalsimr::run_app()
```

If using the app repeatedly, it may be useful to change some of the options in the application to suit your needs. See the vignette "ordinalsimr-options" for more information, `vignette("ordinalsimr-options", package = "ordinalsimr")`.


## Recommendations

Simulations with 1000s of iterations *will* take minutes to hours to run. This should generally be ok on the Shiny app, but if you encounter issues, consider running the simulations in a separate R session using the functions provided in this package (rather than the Shiny app). See the vignette "coding-simulations" for more information, `vignette("coding-simulations", package = "ordinalsimr")`.





Owner

  • Name: Pat
  • Login: NeuroShepherd
  • Kind: user

Citation (CITATION.cff)

# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "ordinalsimr" in publications use:'
type: software
license: MIT
title: 'ordinalsimr: Compare Ordinal Endpoints Using Simulations'
version: 0.2.2
doi: 10.5281/zenodo.14697215
identifiers:
- type: doi
  value: 10.32614/CRAN.package.ordinalsimr
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' application allows users to simulate
  outcomes given different ordinal data distributions.
authors:
- family-names: Callahan
  given-names: Pat
  email: patricktcallahan18@gmail.com
  orcid: https://orcid.org/0000-0003-1769-7580
preferred-citation:
  type: generic
  title: ordinalsimr
  authors:
  - family-names: Callahan
    given-names: Pat
    email: patricktcallahan18@gmail.com
    orcid: https://orcid.org/0000-0003-1769-7580
  doi: 10.5281/zenodo.14697215
  year: '2025'
  month: '1'
  url: https://github.com/neuroshepherd/ordinalsimr
  date-accessed: '2025-01-19'
  copyright: MIT
  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.
repository: https://CRAN.R-project.org/package=ordinalsimr
repository-code: https://github.com/NeuroShepherd/ordinalsimr
url: https://neuroshepherd.github.io/ordinalsimr/
contact:
- family-names: Callahan
  given-names: Pat
  email: patricktcallahan18@gmail.com
  orcid: https://orcid.org/0000-0003-1769-7580
keywords:
- ordinal
- r
- shiny
references:
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  abstract: 'assertthat: Easy Pre and Post Assertions'
  notes: Imports
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  year: '2025'
  doi: 10.32614/CRAN.package.bslib
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  abstract: 'callr: Call R from R'
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  abstract: 'ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics'
  notes: Imports
  url: https://ggplot2.tidyverse.org
  repository: https://CRAN.R-project.org/package=ggplot2
  authors:
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    given-names: Hadley
    email: hadley@posit.co
    orcid: https://orcid.org/0000-0003-4757-117X
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    given-names: Winston
    orcid: https://orcid.org/0000-0002-1576-2126
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    given-names: Lionel
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    given-names: Thomas Lin
    email: thomas.pedersen@posit.co
    orcid: https://orcid.org/0000-0002-5147-4711
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    given-names: Kohske
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    orcid: https://orcid.org/0000-0002-3385-7233
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    orcid: https://orcid.org/0000-0002-9335-7468
  year: '2025'
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  title: golem
  abstract: 'golem: A Framework for Robust Shiny Applications'
  notes: Imports
  url: https://thinkr-open.github.io/golem/
  repository: https://CRAN.R-project.org/package=golem
  authors:
  - family-names: Fay
    given-names: Colin
    email: contact@colinfay.me
    orcid: https://orcid.org/0000-0001-7343-1846
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    email: vincent@thinkr.fr
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  notes: Imports
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  repository: https://CRAN.R-project.org/package=rhandsontable
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    given-names: Jonathan
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  notes: Imports
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  repository: https://CRAN.R-project.org/package=rlang
  authors:
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    given-names: Lionel
    email: lionel@posit.co
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  notes: Imports
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  repository: https://CRAN.R-project.org/package=rms
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    given-names: Frank E
    email: fh@fharrell.com
  year: '2025'
  doi: 10.32614/CRAN.package.rms
- type: software
  title: shiny
  abstract: 'shiny: Web Application Framework for R'
  notes: Imports
  url: https://shiny.posit.co/
  repository: https://CRAN.R-project.org/package=shiny
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    given-names: Winston
    email: winston@posit.co
    orcid: https://orcid.org/0000-0002-1576-2126
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    given-names: Joe
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  year: '2025'
  doi: 10.32614/CRAN.package.shiny
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  abstract: 'shinycssloaders: Add Loading Animations to a ''shiny'' Output While It''s
    Recalculating'
  notes: Imports
  url: https://daattali.com/shiny/shinycssloaders-demo/
  repository: https://CRAN.R-project.org/package=shinycssloaders
  authors:
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    email: daattali@gmail.com
    orcid: https://orcid.org/0000-0002-5645-3493
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  abstract: 'shinyWidgets: Custom Inputs Widgets for Shiny'
  notes: Imports
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  repository: https://CRAN.R-project.org/package=shinyWidgets
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    given-names: Victor
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  title: stats
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  institution:
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  abstract: 'tidyr: Tidy Messy Data'
  notes: Imports
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  notes: Imports
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  notes: Suggests
  url: https://yihui.org/knitr/
  repository: https://CRAN.R-project.org/package=knitr
  authors:
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    given-names: Yihui
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  notes: Suggests
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  authors:
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    given-names: Hadley
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  year: '2025'
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GitHub Events

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  • Create event: 39
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  • Pull request authors: 1
  • Average comments per issue: 0.1
  • Average comments per pull request: 0.13
  • Merged pull requests: 52
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • NeuroShepherd (59)
  • teunbrand (1)
  • luzia1810 (1)
Pull Request Authors
  • NeuroShepherd (168)
Top Labels
Issue Labels
enhancement (7) documentation (4) required (2) questionable feature (1)
Pull Request Labels
documentation (1) enhancement (1)

Packages

  • Total packages: 1
  • Total downloads:
    • cran 225 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 4
  • Total maintainers: 1
cran.r-project.org: ordinalsimr

Compare Ordinal Endpoints Using Simulations

  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 225 Last month
Rankings
Dependent packages count: 27.3%
Dependent repos count: 33.6%
Average: 49.2%
Downloads: 86.8%
Last synced: 7 months ago

Dependencies

DESCRIPTION cran
  • DT * imports
  • assertthat * imports
  • coin * imports
  • config >= 0.3.1 imports
  • dplyr * imports
  • ggplot2 * imports
  • glue * imports
  • golem >= 0.4.0 imports
  • magrittr * imports
  • rhandsontable * imports
  • rms * imports
  • shiny >= 1.7.4 imports
  • shinydashboardPlus * imports
  • stats * imports
  • tidyr * imports
.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v4 composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/pkgdown.yaml actions
  • JamesIves/github-pages-deploy-action v4.5.0 composite
  • actions/checkout v4 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/shiny-deploy-main.yaml actions
  • actions/checkout v4 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-renv v2 composite