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+# ------------------------------------------------------------------------------
+# File: TwoProportionResamplingTest.R
+# Authors: Camille Fairbourn, Scott Manski
+# Date: 01/21/2019
+# Desc:
+# Published Location:
+# Email: fairbour@msu.edu, manskisc@msu.edu
+#
+# For questions or concerns, please email the authors. This work is licensed
+# under a Creative Commons Attribution-ShareAlike 4.0 International License
+# (https://creativecommons.org/licenses/by-sa/4.0/).
+# ------------------------------------------------------------------------------
+
+
+# loading packages
+library(shiny)
+library(ggplot2)
+library(dplyr)
+library(BHH2)
+library(gridExtra)
+library(shinyjs)
+
+enableBookmarking(store = "server")
+
+# Sources objects, functions, etc, from TwoProportionSource.R
+# This file contains the html code for the editable table,
+# the decimalcount function, and the dotplot_locs function.
+source("TwoProportionSource.R")
+
+# defines the presets
+Presets <- list()
+# Presets`preset name` <- c(Top Left, Bottom Left, Top Right, Bottom Right,
+# Column A Name, Column B name, Row A name, Row B name)
+Presets$`Duct Tape Therapy` <- c(22, 15, 4, 10, "Wart Gone", "Wart Remains",
+ "Duct Tape", "Cryotherapy")
+Presets$`Gender Discrimination` <- c(21, 14, 3, 10, "Promotion", "No Promotion",
+ "Male", "Female")
+Presets$`Opportunity Cost` <- c(56, 41, 19, 34, "buy DVD", "not buy DVD",
+ "control", "treatment")
+Presets$`Avandia` <- c(2593, 5386, 65000, 154592, "Yes", "No", "Rosiglitazone",
+ "Pioglitazone")
+Presets$`Custom` <- c("", "", "", "", "Column A", "Column B", "Row 1", "Row 2")
+
+
+ui <- function(request) {
+ fluidPage(useShinyjs(),
+ titlePanel("Two Proportion Resampling Test"),
+ sidebarLayout(
+ sidebarPanel(
+ tabsetPanel(
+ tabPanel("Test",
+ tags$div(class="header", checked = NA,
+ tags$p("Enter your data into the table
+ below, or choose one of the data
+ presets. Press the Shuffle button
+ to simulate the results under an
+ independence null model."
+ )
+ ),
+ hr(),
+ selectInput(inputId = "plot",
+ label = "Plot Type",
+ choices = c("Dotplot", "Histogram")),
+ selectInput(inputId = "presets",
+ label = "Presets",
+ selected = names(Presets)[1],
+ choices = names(Presets)),
+ html_table,
+ actionButton(inputId = "Reset", label = "Reset"),
+ numericInput(inputId = "numsamp",
+ label = "Shuffle how many times?",
+ value = 100, min = 1, max = 5000),
+ tags$div(class="header", checked = NA,
+ tags$p("Enter a value from 1 to 5000")),
+ actionButton("Replicate", "Shuffle")
+
+ ),
+ tabPanel("Information",
+ tags$div(class="header", checked = NA,
+ tags$p("Enter the value of your observed difference of proportions in the text
+ under the graph. Selecting 'greater/less than' will highlight the
+ samples that are greater/less than your value."),
+ tags$p("Selecting 'beyond' will highlight the samples that are further away
+ from 0 than your value."),
+ tags$p("Press the Reset button whenever you change the values in the table."),
+ hr(),
+ hr(),
+ tags$p("Written by Scott Manski"),
+ tags$p("This work is licensed under a "),
+ tags$a(href="http://creativecommons.org/licenses/by-sa/4.0/", "Creative Commons Attribution-ShareAlike 4.0 International License"),
+ hr(),
+ bookmarkButton()
+ )
+ ))),
+
+ mainPanel(
+ plotOutput("RandomPlot1"),
+ checkboxInput("Show.Observed", "Show observed difference", FALSE),
+ textOutput("Observed.Diff"),
+ fluidRow(
+ column(textOutput("count.samples"), width = 3),
+ column(selectInput("inequality", NULL, c("greater than", "less than", "beyond")), width = 3),
+ column(textInput("cutoff", NULL), width = 4),
+ htmlOutput("counts"))
+ )
+ )
+)}
+
+
+
+server <- function(input, output, session) {
+ # initialize values for use in server
+ values <- reactiveValues()
+ values$props <- vector()
+ values$table <- matrix(rep(NA, 9), ncol=3)
+
+ # colors for plots
+ values$hist.fill.color <- "grey70" # histogram bar fill color
+ values$hist.outline.color <- "black" # histogram bar outline color
+ values$dot.fill.color <- "grey70" # dotplot dot fill color
+ values$cutoff.color <- "#F05133" # color for cutoff values
+
+ # theme for plots
+ plaintheme <- theme_bw() +
+ theme(plot.background = element_blank(),
+ panel.grid.major = element_blank(),
+ panel.grid.minor = element_blank() ) +
+ theme(axis.line.x = element_line(color="black", size = 1),
+ axis.line.y = element_line(color="black", size = 1)) +
+ theme(legend.position = "none", plot.margin = margin(10, 10, 10, 10))
+
+ # axis theme for plots
+ axistheme <- theme(plot.title = element_text(hjust = 0.5, color = "black",
+ face = "bold", size=20)) +
+ theme(axis.title = element_text(color = "black", size = 16)) +
+ theme(axis.text.x = element_text(size = 14, color = "black")) +
+ theme(axis.text.y = element_text(size = 14, color = "black"))
+
+ # observe any changes in table
+ observe({
+ values$table[1, 1] <- as.numeric(input$TL) # top left position
+ values$table[1, 2] <- as.numeric(input$TR) # top right position
+ values$table[2, 1] <- as.numeric(input$BL) # bottom left position
+ values$table[2, 2] <- as.numeric(input$BR) # bottom right position
+ values$table[1, 3] <- as.numeric(input$TL) + as.numeric(input$TR) #top sum
+ values$table[2, 3] <- as.numeric(input$BL) + as.numeric(input$BR) # bottom sum
+ values$table[3, 1] <- as.numeric(input$TL) + as.numeric(input$BL) # left sum
+ values$table[3, 2] <- as.numeric(input$TR) + as.numeric(input$BR) # right sum
+ values$table[3, 3] <- as.numeric(input$TL) + as.numeric(input$TR) + # total sum
+ as.numeric(input$BL) + as.numeric(input$BR)
+
+ # calculates the limits for the plots based on the standard deviation
+ # the standard deviation is calculated based on the Hypergeometric distribution
+ values$x.lim <- 6*sqrt(values$table[3, 1]*values$table[1, 3]/values$table[3, 3]*
+ values$table[2, 3]/values$table[3, 3]*values$table[3, 2]/(values$table[3,3]-1)/values$table[1, 3]^2 +
+ values$table[3, 2]*values$table[2, 3]/values$table[3, 3]*
+ values$table[1, 3]/values$table[3, 3]*values$table[3, 1]/(values$table[3,3]-1)/values$table[2, 3]^2)
+ })
+
+ # output for values of table if there is a change
+ output$TRT <- renderText({
+ values$table[1, 3]
+ })
+ output$TRB <- renderText({
+ values$table[2, 3]
+ })
+ output$TBL <- renderText({
+ values$table[3, 1]
+ })
+ output$TBR <- renderText({
+ values$table[3, 2]
+ })
+ output$Total <- renderText({
+ values$table[3, 3]
+ })
+
+
+
+
+ # these will update each time the user clicks the Replicate button
+ observeEvent(input$Replicate || input$Show.Observed, {
+ values$observed <- values$table[1 ,1]/values$table[1, 3] -
+ values$table[2 ,1]/values$table[2, 3]
+ })
+
+
+ # reset the values if "Reset" is pressed
+ observeEvent(input$Reset, {
+ values$props <- vector()
+ enable("Replicate")
+ })
+
+ # checks to see if the current table matches a preset, otherwise the preset is "Custom"
+ observeEvent(c(input$TL, input$TR, input$BL, input$BR, input$C1N,
+ input$C2N, input$R1N, input$R2N), {
+ # combine the current table inputs into a vector
+ current <- c(input$TL, input$BL, input$TR, input$BR, input$C1N, input$C2N,
+ input$R1N, input$R2N)
+ # loops through each preset and determines the number of cells that match the current table
+ preset <- unlist(lapply(names(Presets), function(i) {
+ sum(Presets[[i]] == current)
+ }))
+
+ # if all cells match, change the SelectInput value to that preset,
+ # otherwise change the value to "Custom"
+ if (sum(preset == 8) > 0) {
+ updateSelectInput(session, "presets", selected = names(Presets)[which(preset == 8)])
+ } else {
+ updateSelectInput(session, "presets", selected = "Custom")
+ }
+ }, ignoreInit = TRUE)
+
+
+ # disable or enable the "Shuffle" button
+ # the "Shuffle" button in enabled when the number of shuffles is less than
+ # 5,000 and the total number of shuffles is less than 20,000
+ observeEvent(input$numsamp, {
+ if (is.numeric(input$numsamp)){
+ if (input$numsamp > 5000){
+ disable("Replicate")
+ } else if (length(values$props) <= 20000){
+ enable("Replicate")
+ }
+ }
+ })
+
+ # update the values when shuffle is pressed
+ observeEvent(input$Replicate, {
+ new.vals <- rhyper(input$numsamp, values$table[1, 3],
+ values$table[2, 3], values$table[3, 1])
+ new.vals <- new.vals/values$table[1, 3] - (values$table[3, 1]-new.vals)/
+ values$table[2, 3]
+ values$props <- c(values$props, new.vals)
+
+ if (length(values$props) >= 20000){
+ disable("Replicate")
+ } else {
+ enable("Replicate")
+ }
+ }, ignoreInit = TRUE)
+
+ # when "Beyond" is selected, this function is used to calculate the probability
+ # for each possible outcome.
+ two_sided_values <- function() {
+ m <- values$table[1, 3]
+ n <- values$table[2, 3]
+ k <- values$table[3, 1]
+ support <- c(max(0, k - n):min(k, m))
+ x <- dhyper(support, m, n, k)
+ names(x) <- support
+ x
+ }
+
+ # update the counts for the cutoff if there are any changes
+ update_counts <- eventReactive(c(input$cutoff, input$Replicate, input$Reset,
+ input$inequality, input$presets), {
+ if (!is.na(as.numeric(input$cutoff))){
+ # the error is used to handle rounded values of input$cutoff
+ num.decimals <- decimalcount(as.character(input$cutoff))
+ error <- ifelse(num.decimals <= 1, 0, 0.1^num.decimals/2)
+
+ # for "greater than", finds the number and proportion of values greater than
+ # input$cutoff - error. For "less than", finds the number and proportion of
+ # values less than input$cutoff + error. For beyond, the number and proportion
+ # of values is calculated by adding up all points such that the probability of
+ # obtaining that point is less than or equal to that of input$cutoff see
+ # https://en.wikipedia.org/wiki/Fisher%27s_exact_test, the second to last paragraph
+ # in the Example section)
+ if (input$inequality == "greater than"){
+ values$prob <- sum(values$props >= as.numeric(input$cutoff)-error)/
+ length(values$props)
+ values$count <- sum(values$props >= as.numeric(input$cutoff)-error)
+ } else if (input$inequality == "less than") {
+ values$prob <- sum(values$props <= as.numeric(input$cutoff)+error)/
+ length(values$props)
+ values$count <- sum(as.numeric(values$props) <=
+ as.numeric(input$cutoff)+error)
+ } else {
+ x <- two_sided_values()
+ cutoff <- x[which(names(x) == values$table[1, 1])]
+ vals <- as.numeric(names(x)[which(x <= cutoff)])
+ vals <- vals/values$table[1, 3] - (values$table[3, 1]-vals)/
+ values$table[2, 3]
+
+ values$prob <- length(which(values$props %in% vals))/
+ length(values$props)
+
+ values$count <- length(which(values$props %in% vals))
+ }
+ }
+ })
+
+ # create the desifill.color plot
+ output$RandomPlot1 <- renderPlot({
+ #update_vals()
+ if (length(values$props) != 0 & !is.na(values$table[3, 1])){ # after reset, values$props is empty
+ DF <- values$table
+
+ if (input$plot == "Dotplot"){ # plot == TRUE is dotplot, FALSE is histogram
+ # n is the number of columns for the dotplot
+ # large datasets will have n <- 1
+ if (DF[3, 1] > 1000){
+ n <- 1
+ } else {
+ n <- 4
+ }
+ df <- dotplot_locs(values$props, n, input$cutoff, values$cutoff.color,
+ values$dot.fill.color, input$inequality)
+ df <- df[df$x < values$x.lim & df$x > -values$x.lim, ]
+
+ myplot <- ggplot(df) +
+ geom_point(aes(x ,y, colour = fill.color),
+ size=min(n, 50/length(values$props)^0.5)) +
+ scale_colour_manual(name = "fill.color",
+ values = levels(df$fill.color)) +
+ scale_y_continuous(limits = c(0, max(n*7.5,max(df$y)))) +
+ scale_x_continuous(limits = c(-values$x.lim, values$x.lim)) +
+ labs(x = "Shuffled Difference in Proportions", y = "Count") +
+ plaintheme + axistheme
+ } else {
+ df <- data.frame("x" = values$props[values$props < values$x.lim &
+ values$props > -values$x.lim])
+
+ unique.vals <- sort(unique(as.numeric(as.character(df$x))))
+ myplot <- ggplot(df, aes(x=x)) + geom_histogram(binwidth = max(diff(unique.vals))) +
+ scale_x_continuous(limits = c(-values$x.lim, values$x.lim))
+ names.counts <- ggplot_build(myplot)$data[[1]]$x
+ if (!is.na(as.numeric(input$cutoff))){
+ num.decimals <- decimalcount(as.character(input$cutoff))
+ error <- ifelse(num.decimals <= 2, 0, 0.1^num.decimals/2)
+ if (input$inequality == "greater than"){
+ to.color <- which(names.counts >= as.numeric(input$cutoff)-error)
+ } else if (input$inequality == "less than"){
+ to.color <- which(names.counts <= as.numeric(input$cutoff)+error)
+ } else{
+ to.color <- c(which(names.counts <= -1*abs(as.numeric(input$cutoff))+error),
+ which(names.counts >= abs(as.numeric(input$cutoff))-error))
+ }
+ } else {
+ to.color <- NA
+ }
+ fill.color <- rep(values$hist.fill.color, length(names.counts))
+ fill.color[to.color] <- values$cutoff.color
+ myplot <- ggplot(df, aes(x=x)) +
+ geom_histogram(binwidth = max(diff(unique.vals)), fill = fill.color,
+ col = values$hist.outline.color) +
+ labs(x = "Shuffled Difference in Proportions", y = "Count") +
+ scale_x_continuous(limits = c(-values$x.lim, values$x.lim)) +
+ plaintheme + axistheme
+ }
+ myplot
+ }
+ })
+
+ # calculate the observed difference when checkbox is TRUE
+ output$Observed.Diff <- renderText({
+ if (input$Show.Observed){
+ DF <- data()
+ values$observed = values$table[1, 1]/values$table[1, 3] - values$table[2, 1]/values$table[2, 3]
+ paste("Observed Difference:", round(values$observed, 6))
+ }
+ })
+
+ # text for sample counts
+ output$count.samples <- renderText({
+ "Count Samples"
+ })
+
+ # counts when cutoff is specified
+ output$counts <- renderText({
+ update_counts()
+ if (!is.null(values$prob)){
+ if (is.na(values$prob)){
+ " "
+ } else if (!is.na(as.numeric(input$cutoff))){
+ paste("<font color=", values$cutoff.color, "><b>",values$count, "/",
+ length(values$props), " (", round(values$prob, 4), ")",
+ "</b></font>", sep = "")
+ } else if (nchar(input$cutoff)!=0){
+ "<font color=\"#FF0000\"><b>Invalid Cutoff!</b></font>"
+ } else {
+ " "
+ }
+ }
+ })
+
+ # presets for the contingency table
+ observeEvent(input$presets, {
+ values$props <- vector()
+ enable("Replicate")
+
+ if (input$presets != "Custom") {
+ preset_index <- which(names(Presets) == input$presets)
+ preset <- Presets[[preset_index]]
+ DF <- data.frame("X1" = as.numeric(preset[1:2]),
+ "X2" = as.numeric(preset[3:4]))
+ DF[3, ] <- apply(DF, 2, sum)
+ DF[, 3] <- apply(DF, 1, sum)
+ values$table <- DF
+ values$table.names <- preset[5:8]
+
+ updateTextInput(session, "TL", value = values$table[1,1])
+ updateTextInput(session, "TR", value = values$table[1,2])
+ updateTextInput(session, "BL", value = values$table[2,1])
+ updateTextInput(session, "BR", value = values$table[2,2])
+ updateTextInput(session, "C1N", value = values$table.names[1])
+ updateTextInput(session, "C2N", value = values$table.names[2])
+ updateTextInput(session, "R1N", value = values$table.names[3])
+ updateTextInput(session, "R2N", value = values$table.names[4])
+ }
+ })
+
+ # when the bookmark button is pressed, the current values of props and table are saved
+ onBookmark(function(state) {
+ state$values$props <- values$props
+ state$values$table <- values$table
+ })
+
+ # when opening a bookmarked page, props is restored
+ onRestored(function(state) {
+ values$props <- state$values$props
+ })
+
+ # when opening a bookmarked page, table is restored
+ onRestore(function(state) {
+ values$table <- state$values$table
+ })
+
+
+
+}
+
+shinyApp(ui = ui, server = server, options = list(height = 1080), enableBookmarking = "server")
\ No newline at end of file