shiny module server for roc analysis
rocModule( input, output, session, data, data_label, data_varStruct = NULL, nfactor.limit = 10, design.survey = NULL, id.cluster = NULL )
input | input |
---|---|
output | output |
session | session |
data | Reactive data |
data_label | Reactuve data label |
data_varStruct | Reactive List of variable structure, Default: NULL |
nfactor.limit | nlevels limit in factor variable, Default: 10 |
design.survey | Reactive survey data. default: NULL |
id.cluster | Reactive cluster variable if marginal model, Default: NULL |
shiny module server for roc analysis
shiny module server for roc analysis
library(shiny) library(DT) library(data.table) library(jstable) library(ggplot2) library(pROC) ui <- fluidPage( sidebarLayout( sidebarPanel( rocUI("roc") ), mainPanel( plotOutput("plot_roc"), tableOutput("cut_roc"), ggplotdownUI("roc"), DTOutput("table_roc") ) ) ) server <- function(input, output, session) { data <- reactive(mtcars) data.label <- reactive(jstable::mk.lev(data1)) out_roc <- callModule(rocModule, "roc", data = data, data_label = data.label, data_varStruct = NULL ) output$plot_roc <- renderPlot({ print(out_roc()$plot) }) output$cut_roc <- renderTable({ print(out_roc()$cut) }) output$table_roc <- renderDT({ datatable(out_roc()$tb, rownames = F, editable = F, extensions = "Buttons", caption = "ROC results", options = c(jstable::opt.tbreg("roctable"), list(scrollX = TRUE)) ) }) }