--- title: "Using {ordinalsimr}" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Using {ordinalsimr}} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ``` ```{r setup} library(ordinalsimr) ``` # Shiny App The {ordinalsimr} package wraps a Shiny application and supporting functions for running simulation studies on several pre-selected statistical tests applicable to ordinal data. The Shiny app is particularly suited for calculating Power and Type II error for a proposed 2-group comparison of an ordinal endpoint. Available parameters to manipulate before running the tests include: * Number of simulations to run (integer) * The sample size (integer) * The distribution ratio between group 1 and group 2 (ratio of form X:X) * Group 1 and Group 2 distribution probabilities for levels of the ordinal outcome In addition to these parameters for running the simulation, the following can be adjusted in the Distributions page * Setting the alpha significance level/p-value threshold * Setting the confidence intervals for the Power/T2 Error calculations * Setting the confidence intervals (separately) for the Type I Error in Group 1 and Group 2 Bug reports and feature requests can be submitted as issues at [https://github.com/NeuroShepherd/ordinalsimr/issues](https://github.com/NeuroShepherd/ordinalsimr/issues) ## Using Downloaded Data Data downloaded after running a simulation is stored as a `.rds` file, and can be loaded into your R session using `readRDS()`. The data is structured as a named list with 3 elements at the top level, and several sub-elements. A summary of the available information is available in the code below. ```{r} output <- readRDS("data-2025-01-19-d8621b-1.rds") output$comparison_data$distribution_statistics str(output, max.level = 2) ``` * Top level items * `comparison_data` are results from comparing Group 1 against Group 2 in the statistical tests (for TII error and power) * `group1_data` are results from comparing Group 1 data against itself (for TI error of this group) * `group2_data` are results from comparing Group 2 data against itself (for TI error of this group) * Second level items * `run_info` are tables of detailed metainformation about the parameters used for each run * `distribution_statistics` are tables of computed TII error, power, and associated confidence intervals * `group1_t1error` and `group2_t1error` are tables of TI error and associated confidence intervals