mirror of
https://github.com/agdamsbo/FreesearchR.git
synced 2026-06-19 04:27:30 +02:00
feat: collapsed options and alert when no missings
This commit is contained in:
parent
1b31743898
commit
13c5603245
1 changed files with 174 additions and 154 deletions
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@ -9,45 +9,49 @@
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data_missings_ui <- function(id, ...) {
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ns <- shiny::NS(id)
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list(
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bslib::layout_sidebar(
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sidebar = bslib::sidebar(
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bslib::accordion(
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id = ns("acc_mis"),
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open = "acc_chars",
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multiple = FALSE,
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bslib::accordion_panel(
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value = "acc_pan_mis",
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title = "Settings",
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icon = bsicons::bs_icon("gear"),
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list(bslib::layout_sidebar(
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uiOutput(outputId = ns("feedback")),
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sidebar = bslib::sidebar(
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bslib::accordion(
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id = ns("acc_mis"),
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open = "acc_chars",
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multiple = FALSE,
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bslib::accordion_panel(
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value = "acc_pan_mis",
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title = "Settings",
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icon = bsicons::bs_icon("gear"),
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shiny::conditionalPanel(
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condition = "output.missings == true",
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shiny::uiOutput(ns("missings_method")),
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shiny::uiOutput(ns("missings_var")),
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shiny::helpText(i18n$t("Evaluate missingness by either comparing missing values across variables (optionally grouped by af categorical or dichotomous variable) or compare variables grouped by the missing status (missing or not) of an outcome variable. If there is a significant difference i the missingness, this may cause a bias in you data and should be considered carefully interpreting the data and analyses as data may not be missing at random.")),
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shiny::br(),
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shiny::actionButton(
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inputId = ns("act_miss"),
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label = i18n$t("Evaluate"),
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width = "100%",
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icon = shiny::icon("calculator"),
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disabled = FALSE
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ns = ns
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),
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shiny::helpText(
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i18n$t(
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"Evaluate missingness by either comparing missing values across variables (optionally grouped by af categorical or dichotomous variable) or compare variables grouped by the missing status (missing or not) of an outcome variable. If there is a significant difference i the missingness, this may cause a bias in you data and should be considered carefully interpreting the data and analyses as data may not be missing at random."
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)
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),
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do.call(
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bslib::accordion_panel,
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c(
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list(
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title = "Download",
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icon = bsicons::bs_icon("file-earmark-arrow-down")
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),
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table_download_ui(id = ns("tbl_dwn"), title = NULL)
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)
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shiny::br(),
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shiny::actionButton(
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inputId = ns("act_miss"),
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label = i18n$t("Evaluate"),
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width = "100%",
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icon = shiny::icon("calculator"),
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disabled = FALSE
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)
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)
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),
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...,
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gt::gt_output(outputId = ns("missings_table"))
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)
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)
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),
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do.call(bslib::accordion_panel, c(
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list(
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title = "Download",
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icon = bsicons::bs_icon("file-earmark-arrow-down")
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),
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table_download_ui(id = ns("tbl_dwn"), title = NULL)
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))
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)
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),
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...,
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gt::gt_output(outputId = ns("missings_table"))
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))
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}
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## This should really just be rebuild to only contain a function
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@ -59,46 +63,65 @@ data_missings_ui <- function(id, ...) {
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#' @name data-missings
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#' @returns shiny server module
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#' @export
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data_missings_server <- function(id,
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data,
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max_level = 20,
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...) {
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data_missings_server <- function(id, data, max_level = 20, ...) {
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shiny::moduleServer(
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id = id,
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module = function(input, output, session) {
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ns <- session$ns
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datar <- if (is.reactive(data)) data else reactive(data)
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datar <- if (is.reactive(data))
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data
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else
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reactive(data)
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rv <- shiny::reactiveValues(
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data = NULL,
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table = NULL
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rv <- shiny::reactiveValues(data = NULL,
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table = NULL,
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feedback = NULL)
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## Case with no missings
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info_alert <- shinyWidgets::alert(
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status = "info",
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phosphoricons::ph("question"),
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i18n$t("You have provided a complete dataset with no missing values.")
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)
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output$missings <- shiny::reactive({
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shiny::req(data())
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any(is.na(data()))
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})
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shiny::outputOptions(output, "missings", suspendWhenHidden = FALSE)
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observe({
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shiny::req(data())
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if (!any(is.na(data()))) {
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rv$feedback <- info_alert
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} else {
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rv$feedback <- NULL
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}
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})
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output$feedback <- renderUI(rv$feedback)
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## Notes
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##
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## Code export is still missing
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## Direct table export would be nice
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shiny::observe(
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output$missings_method <- shiny::renderUI({
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shiny::req(data())
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vectorSelectInput(
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inputId = ns("missings_method"),
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label = i18n$t("Analysis method for missingness overview"),
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choices = setNames(
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c(
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"predictors",
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"outcome"
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),
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c(
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i18n$t("Overview of missings across variables"),
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i18n$t("Overview of difference in variables by missing status in outcome")
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)
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shiny::observe(output$missings_method <- shiny::renderUI({
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shiny::req(data())
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vectorSelectInput(
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inputId = ns("missings_method"),
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label = i18n$t("Analysis method for missingness overview"),
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choices = setNames(c("predictors", "outcome"), c(
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i18n$t("Overview of missings across variables"),
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i18n$t(
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"Overview of difference in variables by missing status in outcome"
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)
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)
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})
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)
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))
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)
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}))
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shiny::observe({
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output$missings_var <- shiny::renderUI({
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@ -125,94 +148,93 @@ data_missings_server <- function(id,
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})
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shiny::observeEvent(
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list(input$act_miss),
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{
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shiny::req(datar())
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shiny::req(input$missings_var)
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# browser()
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df_tbl <- datar()
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by_var <- input$missings_var
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shiny::observeEvent(list(input$act_miss), {
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shiny::req(datar())
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shiny::req(input$missings_var)
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# browser()
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df_tbl <- datar()
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by_var <- input$missings_var
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parameters <- list(
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by_var = by_var,
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max_level = max_level,
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type = input$missings_method
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)
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parameters <- list(
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by_var = by_var,
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max_level = max_level,
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type = input$missings_method
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)
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tryCatch(
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{
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shiny::withProgress(message = i18n$t("Calculating. Hold tight for a moment.."), {
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out <- do.call(
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compare_missings,
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modifyList(parameters, list(data = df_tbl))
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)
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})
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},
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error = function(err) {
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showNotification(paste0("Error: ", err), type = "err")
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}
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)
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tryCatch({
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shiny::withProgress(message = i18n$t("Calculating. Hold tight for a moment.."), {
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out <- do.call(compare_missings, modifyList(parameters, list(data = df_tbl)))
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})
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}, error = function(err) {
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showNotification(paste0("Error: ", err), type = "err")
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})
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if (is.null(input$missings_var) || input$missings_var == "" || !input$missings_var %in% names(datar()) || input$missings_var == "none") {
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# if (is.null(variabler()) || variabler() == "" || !variabler() %in% names(data()) || variabler() == "none") {
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# tbl <- rv$data()
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if (anyNA(datar())) {
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if (input$missings_method == "predictors") {
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title <- i18n$t("Overview of missing observations")
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} else {
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title <- i18n$t("No outcome measure chosen")
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}
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if (is.null(input$missings_var) ||
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input$missings_var == "" ||
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!input$missings_var %in% names(datar()) ||
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input$missings_var == "none") {
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# if (is.null(variabler()) || variabler() == "" || !variabler() %in% names(data()) || variabler() == "none") {
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# tbl <- rv$data()
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if (anyNA(datar())) {
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if (input$missings_method == "predictors") {
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title <- i18n$t("Overview of missing observations")
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} else {
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title <- i18n$t("No missing observations")
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title <- i18n$t("No outcome measure chosen")
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}
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} else {
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## Due to reactivity, the table updates too quickly. this mitigates that issue..
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title <- i18n$t("No missing observations")
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}
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} else {
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## Due to reactivity, the table updates too quickly. this mitigates that issue..
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if (input$missings_var == "predictors") {
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title <- glue::glue(i18n$t("Missings across variables by the variable **'{input$missings_var}'**"))
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} else {
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title <- glue::glue(i18n$t("Missing vs non-missing observations in the variable **'{input$missings_var}'**"))
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}
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if (input$missings_var == "predictors") {
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title <- glue::glue(
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i18n$t(
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"Missings across variables by the variable **'{input$missings_var}'**"
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)
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)
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} else {
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title <- glue::glue(
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i18n$t(
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"Missing vs non-missing observations in the variable **'{input$missings_var}'**"
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)
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)
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}
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}
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attr(out, "tbl_title") <- title
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rv$data <- shiny::reactive(out)
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})
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shiny::observeEvent(list(
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# input$act_miss
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rv$data
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), {
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output$missings_table <- gt::render_gt({
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shiny::req(rv$data)
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# shiny::req(input$missings_var)
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# browser()
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if ("p.value" %in% names(rv$data()[["table_body"]])) {
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tbl <- rv$data() |>
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gtsummary::bold_p()
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} else {
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tbl <- rv$data()
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}
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attr(out, "tbl_title") <- title
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rv$data <- shiny::reactive(out)
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}
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)
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out <- tbl |>
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gtsummary::as_gt() |>
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gt::tab_header(title = gt::md(attr(tbl, "tbl_title")))
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shiny::observeEvent(
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list(
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# input$act_miss
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rv$data
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),
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{
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output$missings_table <- gt::render_gt({
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shiny::req(rv$data)
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# shiny::req(input$missings_var)
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# browser()
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if ("p.value" %in% names(rv$data()[["table_body"]])) {
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tbl <- rv$data() |>
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gtsummary::bold_p()
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} else {
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tbl <- rv$data()
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}
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attr(out, "strat_var") <- input$missings_var
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rv$table <- out
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out <- tbl |>
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gtsummary::as_gt() |>
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gt::tab_header(title = gt::md(attr(tbl, "tbl_title")))
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attr(out, "strat_var") <- input$missings_var
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rv$table <- out
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out
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})
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}
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)
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out
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})
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})
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table_download_server(
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@ -228,25 +250,20 @@ data_missings_server <- function(id,
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missing_demo_app <- function() {
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ui <- do.call(
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bslib::page,
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c(
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list(
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title = i18n$t("Missings"),
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icon = bsicons::bs_icon("x-circle")
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),
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data_missings_ui(id = "data"),
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gt::gt_output("table_p")
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)
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)
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ui <- do.call(bslib::page, c(
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list(
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title = i18n$t("Missings"),
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icon = bsicons::bs_icon("x-circle")
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),
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data_missings_ui(id = "data"),
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gt::gt_output("table_p")
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))
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server <- function(input, output, session) {
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data_demo <- mtcars
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data_demo[sample(1:32, 10), "cyl"] <- NA
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data_demo[sample(1:32, 8), "vs"] <- NA
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rv <- shiny::reactiveValues(
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table = NULL
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)
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rv <- shiny::reactiveValues(table = NULL)
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rv$table <- data_missings_server(id = "data", data = data_demo)
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@ -280,17 +297,15 @@ missing_demo_app <- function() {
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#' @returns gtsummary list object
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#' @export
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#'
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compare_missings <- function(
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data,
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by_var,
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max_level = 20,
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type = c("predictors", "outcome")
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) {
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compare_missings <- function(data,
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by_var,
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max_level = 20,
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type = c("predictors", "outcome")) {
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type <- match.arg(type)
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if (!is.null(by_var) && by_var != "" && by_var %in% names(data)) {
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data <- data |>
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lapply(\(.x){
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lapply(\(.x) {
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if (is.factor(.x)) {
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cut_var(.x, breaks = 20, type = "top")
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} else {
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@ -334,7 +349,7 @@ compare_missings <- function(
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missings_logic_across <- function(data, exclude = NULL) {
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# This function includes a approach way to preserve variable labels
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names(data) |>
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lapply(\(.x){
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lapply(\(.x) {
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# browser()
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# Saving original labels
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lab <- REDCapCAST::get_attr(data[[.x]], attr = "label")
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@ -345,7 +360,12 @@ missings_logic_across <- function(data, exclude = NULL) {
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}
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if (!is.na(lab)) {
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# Restoring original labels, if not NA
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REDCapCAST::set_attr(data = out, label = lab, attr = "label", overwrite = TRUE)
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REDCapCAST::set_attr(
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data = out,
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label = lab,
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attr = "label",
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overwrite = TRUE
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)
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} else {
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out
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}
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