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ordinalsimr

Lifecycle: experimental R-CMD-check CRAN status Codecov test coverage DOI

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:

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

Running the App

The app can be started with the following code:

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").

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.