inst/shinyApps/MethodEvalViewer/ui.R

In ohdsi-studies/MethodsLibraryPleEvaluation: Evaluation of Population-Level Estimation Methods

library(shiny)
library(DT)

shinyUI(
  fluidPage(style = 'width:1000px;',
            titlePanel("OHDSI Population-Level Estimation Method Evaluation"),
            fluidRow(
              column(2,
                     selectInput("evalType", label = span("Evaluation type", title = "Type of task to evaluate."), choices = c("Effect est.", "Comparative effect est.")),
                     selectInput("calibrated", label = span("Empirical calibration", title = "Should empirical calibration be applied before computing performance metrics?"), choices = c("Uncalibrated", "Calibrated")),
                     selectInput("mdrr", label = span("Minimum Detectable RR", title = "Minimum detectable relative risk used to filter the controls before computing performance metrics."), choices = c("All", "4", "2", "1.5", "1.25"), selected = "1.25"),
                     selectInput("db", label = span("Database", title = "The database on which the methods were executed"), choices = dbs),
                     selectInput("stratum", label = span("Stratum", title = "Limiting the performance metrics to a single outcome (for exposure controls) or exposure (for outcome controls)."), choices = strata),
                     selectInput("trueRr", label = span("True effect size", title = "The true effect size to be considered when computing the performance metrics."), choices = trueRrs),
                     checkboxGroupInput("method", label = span("Method", title = "Methods to include in the evaluation."), choices = methods$method)
                     
              ),
              column(10,
                     textOutput("controlCount"),
                     dataTableOutput("performanceMetrics"),
                     div(style="display:inline-block", h4(textOutput("details"))), 
                     div(style="display:inline-block", actionLink("showSettings", "Details")),
                     conditionalPanel(condition = "output.details",
                                      tabsetPanel(
                                        tabPanel("Estimates", 
                                                 uiOutput("hoverInfoEstimates"),
                                                 plotOutput("estimates", 
                                                            height = "200px",
                                                            hover = hoverOpts("plotHoverInfoEstimates", 
                                                                              delay = 100, 
                                                                              delayType = "debounce"))
                                                 ),
                                        tabPanel("ROC curves", plotOutput("rocCurves"))
                                      )
                     )   
              )
            )
  )
)