inst/apps/Design-Verifikation_v0.1.1/attributiv/server_attributiv.R

# testplan output ----------
output$result_sample_size_attributiv <- renderUI({

  # determine minimal sample-size
  for (sample_size in 1:1000){
    #browser()
    if (input$test_power_attributiv/100 < pbinom(q = 0, size = sample_size, prob = (1 - input$p_min_attributiv/100), lower.tail = FALSE)){
      minimal_sample_size <- sample_size
      break;
    }
    minimal_sample_size <- ">1000"
  }

  tags$b("(n =", minimal_sample_size, ", c = 0)", style="align:center;")

  })

# display oc-kurven --------------------
output$oc_kurven_attributiv <- renderPlot({

  oc_data <-
    expand.grid(
      p = seq(0, 1, by = 0.005)*100,
      sample_size = input$n
    ) %>%
    mutate(
      test_plan = paste("(", sample_size, ",",input$c,")", sep = ""),
      p_reject = pbinom(q = input$c, size = sample_size, prob = (1-p/100), lower.tail = FALSE)*100
    )

  oc_data %>%
    ggplot(aes(x = p, y = p_reject)) +
    geom_line() +
    scale_x_continuous("p [%] ('wahre' i.o.-rate des Produktionsprozesses)", breaks = seq(0, 100, by = 5)) +
    scale_y_continuous("Wahrscheinlichkeit für Testergebnis: Design ist n.i.o.", breaks = seq(0, 100, by = 5)) +
    geom_hline(yintercept = input$test_power_attributiv, alpha = 0.5, linetype = "dashed") +
    geom_vline(xintercept = input$p_min_attributiv, alpha = 0.5, linetype = "dashed") +
    geom_text(x = 10, y = input$test_power_attributiv, label = "geforderte Power des Tests", hjust = 0, vjust = 0) +
    geom_text(x = input$p_min_attributiv, y = 95, label = "geforderte minimale i.o.-Rate",  hjust = 0, vjust = 0, angle = -90)



})
stephanGit/leistungstests documentation built on June 13, 2018, 8:24 p.m.