anova

server.r

library(shiny)
library(ggplot2)

# Define server logic required to generate and plot a random distribution
shinyServer(function(input, output) {
  generate_data <- reactive(
    function(){
      mu <- c(input$mu_1, input$mu_2, input$mu_3)
    tmp <- data.frame(len = rnorm(length(mu) * input$n, 
                                  mean = rep(mu, each = input$n), 
                                  sd = input$sigma),
                      dose = rep(c("0.5","1","2"), 
                                 each = input$n))
    tmp$group_avg <- with(tmp, ave(len, dose))
    tmp$overall_avg <- with(tmp, mean(len))
    tmp
  })
  
  output$rawPlot <- reactivePlot(function() {
    print(qplot(len, factor(dose), data = generate_data(),
                colour = dose) +
      facet_wrap(~ dose, scale = "free_y", ncol =1) +
      geom_vline(aes(xintercept = overall_avg), colour = "grey50") +
      geom_vline(aes(xintercept = group_avg,colour = dose)) +
      xlim(limits = range(generate_data()$len)))
  })  
  
  output$total_res <- reactivePlot(function(){
    print(qplot(len - overall_avg, data = generate_data(), fill = dose)+
      xlim(limits = range(generate_data()$len) - generate_data()$overall_avg[1]))  
  })
  
  output$within_res <- reactivePlot(function(){
    print(qplot(len - group_avg, data = generate_data(), fill = dose)+
      xlim(limits = range(generate_data()$len) - generate_data()$overall_avg[1]))   
  })
  
  output$between_res <- reactivePlot(function(){
    print(qplot(group_avg - overall_avg, data = generate_data(), fill = dose)+
      xlim(limits = range(generate_data()$len) - generate_data()$overall_avg[1]))
  })
  
  calc_ss <- reactive(function(){
    with(generate_data(),
         list(total_ss = sum((len - overall_avg)^2),
              total_df = length(len) - 1,
              within_ss = sum((len - group_avg)^2),
              within_df = length(len) - length(unique(dose)),
              between_ss = sum((group_avg - overall_avg)^2),
              between_df = length(unique(dose)) - 1)
         )

  })
  
  output$total_ss <- reactiveText(function(){
    paste("Total sum of squares: ", round(calc_ss()$total_ss,2), 
      "Total df: ", calc_ss()$total_df,
       "MSS total: ", round(calc_ss()$total_ss/calc_ss()$total_df,2))
  })
  output$within_ss <- reactiveText(function(){
    paste("Within sum of squares: ", round(calc_ss()$within_ss,2),
          "Within df: ", calc_ss()$within_df,
          "MSS within: ", round(calc_ss()$within_ss/calc_ss()$within_df,2))
  })  
  output$between_ss <- reactiveText(function(){
    paste("Between sum of squares: ", round(calc_ss()$between_ss,2),
          "Between df: ", calc_ss()$between_df,
          "MSS between: ", round(calc_ss()$between_ss/calc_ss()$between_df,2))
  })  
  
  output$F_stat <- reactiveText(function(){
    paste("F-statistic", round((calc_ss()$between_ss/calc_ss()$between_df)/(calc_ss()$within_ss/calc_ss()$within_df),2))
  })
})

ui.r

library(shiny)

shinyUI(pageWithSidebar(
  headerPanel("Sums of squares in ANOVA"),
  
  sidebarPanel(
    
    sliderInput("mu_1", "mu_1:", value = 13,
                min = 10, max = 40),
    sliderInput("mu_2", "mu_2:", value = 23,
                min = 10, max = 40),
    sliderInput("mu_3", "mu_3:", value = 26,
                min = 10, max = 40),
    sliderInput("sigma", "sigma:", value = 3.75,
                min = 1, max = 20),
    
    numericInput("n", "sample size", 10),
    submitButton("Update View")
  ),
  
  mainPanel(
    h3("Raw data"),
    plotOutput("rawPlot", height = "200px",  width = "400px"),
    h3("Residuals from equal means model"),
    plotOutput("total_res", height = "200px",  width = "400px"),
    textOutput("total_ss"),
    h3("Residuals from separate means model"),
    plotOutput("within_res", height = "200px",  width = "400px"),
    textOutput("within_ss"),
    h3("Deviation of groups averages from overall averages"),
    plotOutput("between_res", height = "200px",  width = "400px"),
    textOutput("between_ss"),
    h3(textOutput("F_stat"))
    
  )
))