Development

.Rbuildignore

@@ -12,3 +12,9 @@ $run_dev.*
 ^\.github$
 ^app\.R$
 ^rsconnect$
+^doc$
+^Meta$
+^_pkgdown\.yml$
+^docs$
+^pkgdown$
+

.github/workflows/pkgdown.yaml

@@ -0,0 +1,48 @@
+# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
+# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
+on:
+  push:
+    branches: [main, master]
+  # pull_request:
+  #   branches: [main, master]
+  release:
+    types: [published]
+  workflow_dispatch:
+
+name: pkgdown
+
+jobs:
+  pkgdown:
+    runs-on: ubuntu-latest
+    # Only restrict concurrency for non-PR jobs
+    concurrency:
+      group: pkgdown-${{ github.event_name != 'pull_request' || github.run_id }}
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+    permissions:
+      contents: write
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/setup-pandoc@v2
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::pkgdown, local::.
+          needs: website
+
+      - name: Build site
+        run: pkgdown::build_site_github_pages(new_process = FALSE, install = FALSE)
+        shell: Rscript {0}
+
+      - name: Deploy to GitHub pages 🚀
+        if: github.event_name != 'pull_request'
+        uses: JamesIves/[email protected]
+        with:
+          clean: false
+          branch: gh-pages
+          folder: docs

.gitignore

@@ -2,3 +2,7 @@
 .Rhistory
 .RData
 .Ruserdata
+inst/doc
+/doc/
+/Meta/
+docs

DESCRIPTION

@@ -34,10 +34,13 @@ Imports:
 Encoding: UTF-8
 LazyData: true
 RoxygenNote: 7.2.3
-URL: https://github.com/NeuroShepherd/ordinalsimr
+URL: https://github.com/NeuroShepherd/ordinalsimr, https://neuroshepherd.github.io/ordinalsimr/
 BugReports: https://github.com/NeuroShepherd/ordinalsimr/issues
 Suggests: 
+    knitr,
+    rmarkdown,
     testthat (>= 3.0.0)
 Config/testthat/edition: 3
 Depends: 
     R (>= 2.10)
+VignetteBuilder: knitr

R/mod_data_entry.R

@@ -28,11 +28,20 @@ mod_data_entry_server <- function(id){
     ns <- session$ns
 
     default_entry_rows <- getOption("ordinalsimr.default_entry_rows", default = 3)
-    entered_data = data.frame(`Group 1 Probabilities` = rep(0, default_entry_rows),
-                              `Group 2 Probabilities` = rep(0, default_entry_rows),
-                              check.names = FALSE)
+    default_dist_option <- getOption("ordinalsimr.default_distributions")
+    default_distribution_data <- data.frame(`Group 1 Probabilities` = rep(0, default_entry_rows),
+                                            `Group 2 Probabilities` = rep(0, default_entry_rows),
+                                            check.names = FALSE)
+    entered_data <- if (is.data.frame(default_dist_option)) {
+      default_dist_option %>%
+        dplyr::rename(`Group 1 Probabilities` = 1,
+                      `Group 2 Probabilities` = 2)
+    } else {
+      default_distribution_data
+    }
     reactive_data_vals <- reactiveVal(entered_data)
 
+
     observeEvent(input$hottable, { reactive_data_vals(hot_to_r(input$hottable)) } )
     observeEvent(input$add_row, { reactive_data_vals(rbind(reactive_data_vals(), 0)) })
     observeEvent(input$delete_row, { reactive_data_vals(reactive_data_vals()[-nrow(reactive_data_vals()), ]) })

R/utils.R

@@ -37,7 +37,7 @@ parse_ratio_text <- function(text) {
 
 #' Calculate Hypothesis Test Parameters
 #'
-#' This function calculates the power, Type II error, and Type I error of tests given p-values. Power, Type II error, and confidence intervals calculated using `stats::binom.test()`.
+#' This function calculates the power, Type II error, and Type I error of tests given p-values. Power, Type II error, and confidence intervals calculated using `stats::binom.test()` which implements the Newcombe method.
 #'
 #' @param df Data frame where each column is a vector of p-values from a statistical test
 #' @param alpha Numeric significance level; defaults to 0.05
@@ -78,7 +78,7 @@ calculate_power_t2error <- function(df, alpha = 0.05, power_confidence_int = 95,
 
 #' Calculate Type 1 Error
 #'
-#' Calculate Type 1 error for a distribution, and the confidence interval around this estimate. Type I error and confidence intervals calculated using `stats::binom.test()`.
+#' Calculate Type 1 error for a distribution, and the confidence interval around this estimate. Type I error and confidence intervals calculated using `stats::binom.test()` which implements the Newcombe method.
 #'
 #' @param df data frame
 #' @param alpha significance level

README.Rmd

@@ -21,7 +21,9 @@ knitr::opts_chunk$set(
 [![CRAN status](https://www.r-pkg.org/badges/version/ordinalsimr)](https://CRAN.R-project.org/package=ordinalsimr)
 <!-- badges: end -->
 
-The goal of ordinalsimr is to ...
+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
 
@@ -32,6 +34,12 @@ You can install the development version of ordinalsimr from [GitHub](https://git
 devtools::install_github("NeuroShepherd/ordinalsimr")
 ```
 
+## Recommendations
+
+The application is available at [link], but may be down due to account usage limitations on ShinyApps.io. There is not currently a plan to increase the usage limits so it is *strongly recommended that you run the application locally*. 
+
+Informative progressive bars have not been implemented in the Shiny application, but a simulation that fails to run will almost always fail at the beginning rather than in the middle of the run. Simulations with 1000s of iterations *will* take minutes to hours to run.
+
 
 
 

README.md

@@ -12,7 +12,22 @@ 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)
 <!-- badges: end -->
 
-The goal of ordinalsimr is to …
+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
 
@@ -23,3 +38,15 @@ You can install the development version of ordinalsimr from
 # install.packages("devtools")
 devtools::install_github("NeuroShepherd/ordinalsimr")
 ```
+
+## Recommendations
+
+The application is available at \[link\], but may be down due to account
+usage limitations on ShinyApps.io. There is not currently a plan to
+increase the usage limits so it is *strongly recommended that you run
+the application locally*.
+
+Informative progressive bars have not been implemented in the Shiny
+application, but a simulation that fails to run will almost always fail
+at the beginning rather than in the middle of the run. Simulations with
+1000s of iterations *will* take minutes to hours to run.

_pkgdown.yml

@@ -0,0 +1,4 @@
+url: https://neuroshepherd.github.io/ordinalsimr/
+template:
+  bootstrap: 5
+

renv.lock

@@ -1887,6 +1887,20 @@
       ],
       "Hash": "3a1f41807d648a908e3c7f0334bf85e6"
     },
+    "shinycssloaders": {
+      "Package": "shinycssloaders",
+      "Version": "1.0.0",
+      "Source": "Repository",
+      "Repository": "CRAN",
+      "Requirements": [
+        "R",
+        "digest",
+        "glue",
+        "grDevices",
+        "shiny"
+      ],
+      "Hash": "f39bb3c44a9b496723ec7e86f9a771d8"
+    },
     "shinydashboard": {
       "Package": "shinydashboard",
       "Version": "0.7.2",

vignettes/.gitignore

@@ -0,0 +1,2 @@
+*.html
+*.R