server_meta.R

# Create the dataset by merging the two tables per patient
  data_set_reactive <- metaReactive({
    event_data_filtered <- event_data %>% dplyr::filter(PARAMCD == !!input$filter_param)
    ads_selected <- pat_data %>% dplyr::select(dplyr::one_of(c(!!input$select_regressor, c("SUBJID", "STUDYID"))))
    merge(ads_selected, event_data_filtered, by = c("SUBJID", "STUDYID"))
  })

  # Create a pure reactive to create the formula shown in the linear model
  formula_reactive <- reactive({
    validate(need(is.character(input$select_regressor), "Cannot work without selected column"))

    stats::as.formula(paste("AVAL", paste(input$select_regressor, collapse = " + "), sep = " ~ "))
  })

  # Create a linear model
  model_reactive <- metaReactive2({
    validate(need(is.data.frame(data_set_reactive()), "Data Set could not be created"))
    validate(need(is.language(formula_reactive()), "Formula could not be created from column selections"))

    metaExpr({
      model_data <- !!data_set_reactive()
      lm(formula = !!formula_reactive(), data = model_data)
    })
  })

  # Plot Regression vs fitted
  output$plot1 <- metaRender(renderPlot, {
    plot(!!model_reactive(), which = 1)
  })

  # show model summary
  output$text1 <- metaRender(renderPrint, {
    !!model_reactive() %>% summary()
  })

  # Show Code to produce the Outputs
  observeEvent(input$show_r_code, {
    showModal(modalDialog(
      title = "R Code",
      tags$pre(
        id = "r_code",
        expandChain(
          library_code,
          data_code,
          output$plot1(),
          output$text1()
        ) %>% formatCode() %>% paste(collapse = "\n")
      ),
      footer = tagList(
        actionButton("copyRCode", "Copy to Clipboard", `data-clipboard-target` = "#r_code"),
        modalButton("Dismiss")
      ),
      size = "l",
      easyClose = TRUE
    ))
  })