Package: ordinalsimr 0.2.4

ordinalsimr: Compare Ordinal Endpoints Using Simulations

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:Pat Callahan [aut, cre, cph]

ordinalsimr_0.2.4.tar.gz
ordinalsimr_0.2.4.zip(r-4.7-any)ordinalsimr_0.2.4.zip(r-4.6-any)ordinalsimr_0.2.4.zip(r-4.5-any)
ordinalsimr_0.2.4.tgz(r-4.6-any)ordinalsimr_0.2.4.tgz(r-4.5-any)
ordinalsimr_0.2.4.tar.gz(r-4.7-any)ordinalsimr_0.2.4.tar.gz(r-4.6-any)
ordinalsimr_0.2.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ordinalsimr/json (API)

# Install 'ordinalsimr' in R:

install.packages('ordinalsimr', repos = c('https://neuroshepherd.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/neuroshepherd/ordinalsimr/issues

Pkgdown/docs site:https://neuroshepherd.github.io

Datasets:

simulation_data_one_group - Simulation Data for One Group
simulation_data_two_groups - Simulation Data for Two Groups

On CRAN:

ordinal shiny

4.52 score 1 stars 22 scripts 255 downloads 12 exports 106 dependencies

Last updated from:be3a192578. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	146
source / vignettes	OK	301
linux-release	OK	142
macos-release	OK	153
macos-oldrel	OK	245
windows-devel	OK	130
windows-release	OK	114
windows-oldrel	OK	127
wasm-release	OK	137

Exports:%>%assign_groups calculate_power_t2error calculate_t1_error get_ordinalsimr_options ordinal_tests parse_ratio_text plot_distribution_results plot_power run_app run_simulations set_ordinalsimr_options

Dependencies:assertthat attempt backports base64enc bslib cachem callr checkmate cli cluster codetools coin colorspace commonmark config cpp11 crosstalk data.table digest dplyr DT evaluate farver fastmap fontawesome foreign Formula fs generics ggplot2 glue golem gridExtra gtable highr Hmisc htmlTable htmltools htmlwidgets httpuv isoband jquerylib jsonlite knitr labeling later lattice lazyeval libcoin lifecycle magrittr MASS Matrix MatrixModels matrixStats memoise mime modeltools multcomp mvtnorm nlme nnet otel pillar pkgconfig polspline processx promises ps purrr quantreg R6 rappdirs RColorBrewer Rcpp rhandsontable rlang rmarkdown rms rpart rstudioapi S7 sandwich sass scales shiny shinycssloaders shinyWidgets sourcetools SparseM stringi stringr survival TH.data tibble tidyr tidyselect tinytex utf8 vctrs viridisLite withr xfun xtable yaml zoo

Using {ordinalsimr}

Shiny App | Data Generation Process | Statistical Tests Used | Practical Script-Based Workflow | Package Architecture

Rendered fromordinalsimr.Rmdusingknitr::rmarkdown

Last update: 2026-02-26
Started: 2024-02-17

{ordinalsimr} Options

Options | What are options? | Changing Options | Automatically Set Options | Non-Required Options | Setting and Getting {ordinalsimr} Options

Rendered fromordinalsimr-options.Rmdusingknitr::rmarkdown

Last update: 2025-01-29
Started: 2025-01-20

Coding Simulations

Rendered fromcoding-simulations.Rmdusingknitr::rmarkdown

Last update: 2025-01-20
Started: 2024-02-27

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Randomly assign groups	assign_groups
Calculate Hypothesis Test Parameters	calculate_power_t2error
Calculate Type 1 Error	calculate_t1_error
Get ordinalsimr options	get_ordinalsimr_options
Ordinal outcome tests	ordinal_tests
Parse Ratio Text	parse_ratio_text
Plot Distribution	plot_distribution_results
Plot Test Power	plot_power
Run the Shiny Application	run_app
Run Simulations	run_simulations
Set ordinalsimr Shiny App Default Values	set_ordinalsimr_options
Simulation Data for One Group	simulation_data_one_group
Simulation Data for Two Groups	simulation_data_two_groups