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rocModule: shiny module server for roc analysis

Source: R/roc.R
rocModule.Rd

shiny module server for roc analysis

Usage

rocModule(
  input,
  output,
  session,
  data,
  data_label,
  data_varStruct = NULL,
  nfactor.limit = 10,
  design.survey = NULL,
  id.cluster = NULL
)

Arguments

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

Value

shiny module server for roc analysis

Details

shiny module server for roc analysis

See also

quantile setkey ggroc geeglm svyglm theme_modern

Examples

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))
    )
  })
}