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Display table on web app
1 parent f33378d commit 656026b

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Lines changed: 226 additions & 50 deletions

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‎.gitignore‎

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# Temporary files created by R markdown
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*.utf8.md
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*.knit.md
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.Rproj.user

‎Block_Randomization/Block_randomization_web_app.R‎

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# This script is the source for a web app to plot block randomization
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# Documentation -----------------------------------------------------------
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# Web app to produce block randomization trials
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# Author: Deepak Sharma
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# Computer Programmer, JPNATC - AIIMS
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# Date: 28 March, 2017
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# Import libraries --------------------------------------------------------
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library(shiny)
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library(psych)
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# Define UI for application that draws a histogram
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# User interface ----------------------------------------------------------
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ui <- fluidPage(
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# Application title
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titlePanel("Block randomization in R"),
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# Sidebar with a slider input for number of bins
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sidebarLayout(
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sidebarPanel(
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sliderInput("trials",
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"Number of trials:",
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min = 1,
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max = 300,
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value = 150),
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sliderInput("blocks",
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"Number of blocks:",
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min = 1,
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max = 10,
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value = 3),
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sliderInput("cases",
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"Number of cases:",
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min = 1,
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max = 4,
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value = 2)
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titlePanel("Block randomization in R"),
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sidebarLayout(
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sidebarPanel(
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sliderInput(
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"trials",
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"Number of trials:",
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min = 1,
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max = 300,
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value = 150
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),
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sliderInput(
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"blocks",
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"Number of blocks:",
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min = 1,
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max = 10,
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value = 3
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),
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# Show a plot of the generated distribution
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mainPanel(
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plotOutput("distPlot")
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sliderInput(
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"cases",
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"Number of cases:",
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min = 1,
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max = 4,
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value = 2
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)
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)
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)
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# Define server logic required to draw a histogram
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server <- function(input, output) {
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output$distPlot <- renderPlot({
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# generate bins based on input$bins from ui.R
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x <- input$blocks
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y <- input$trials
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condition <- block.random( n= input$trials,c(block = input$blocks,drug = 2))
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# draw the histogram with the specified number of bins
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plot(condition[,2], condition[,3], col = 'darkgray', border = 'white')
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})
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),
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# Show result table
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mainPanel(tableOutput("filetable"))
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))
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# Server ------------------------------------------------------------------
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server <- function(input, output)
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{
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output$filetable <- renderTable({
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condition <-
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block.random(n = input$trials, c(block = input$blocks, drug = input$cases))
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output <- data.frame(condition)
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colnames(output) <- c("Block", "to_be_discarded", "Case")
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output[,-2]
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})
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}
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# Run the application
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shinyApp(ui = ui, server = server)
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# Run application ---------------------------------------------------------
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shinyApp(ui = ui, server = server)

‎Block_Randomization/Randomized_trials.csv‎

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"","Block no.","Case"
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"S1",1,2
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"S2",1,2
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"S3",1,1
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"S4",1,2
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"S5",1,1
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"S6",1,1
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"S7",2,2
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"S8",2,1
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"S9",2,1
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"S10",2,2
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"S11",2,2
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"S12",2,1
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"S13",3,1
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"S14",3,1
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"S15",3,2
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"S16",3,1
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"S17",3,2
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"S18",3,2
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"S19",4,2
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"S20",4,1
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"S21",4,2
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"S22",4,1
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"S23",4,2
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"S24",4,1
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"S25",5,1
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"S26",5,2
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"S27",5,2
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"S28",5,1
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"S29",5,2
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"S30",5,1
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"S31",6,1
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"S32",6,1
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"S33",6,2
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"S34",6,2
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"S35",6,1
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"S36",6,2
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"S37",7,1
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"S38",7,2
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"S39",7,2
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"S40",7,2
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"S41",7,1
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"S42",7,1
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"S43",8,1
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"S44",8,2
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"S45",8,1
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"S46",8,2
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"S47",8,2
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"S48",8,1
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"S49",9,2
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"S50",9,2
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"S51",9,1
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"S52",9,1
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"S61",11,1
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"S66",11,2
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"S67",12,1
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"S68",12,1
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"S69",12,1
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"S70",12,2
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"S71",12,2
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"S72",12,2
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"S73",13,2
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"S74",13,1
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"S78",13,1
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"S79",14,2
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"S81",14,2
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"S105",18,1
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"S107",18,1
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"S108",18,2
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"S109",19,2
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"S110",19,1
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"S111",19,2
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"S112",19,1
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"S113",19,2
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"S137",23,2
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"S138",23,1
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"S139",24,2
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"S140",24,1
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"S141",24,2
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"S145",25,1
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"S146",25,1
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"S147",25,2
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"S148",25,2
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"S149",25,1
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"S150",25,2

‎block_randomization.r‎

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install.packages("psych")
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# Include psych package
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library(psych)
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condition <- block.random( n= 150,c(block = 3,drug = 2))
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headTail(condition)
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write.csv(condition,"randomized_design.csv")
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pairs.panels(condition)
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plot(condition,type = 'l')
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# Generate N number of trials ---------------------------------------------
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n <- 150
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not_useful <- 3
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cases <- 2
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# Generate randomized trials for N = 150 ----------------------------------
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trials <- block.random(n,c(not_useful, cases))
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headTail(trials)
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output <- data.frame(trials)
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colnames(output) <- c("Block no.","to_be_discarded","Case")
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# Write CSV file ----------------------------------------------------------
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# Discarding second column which contains non-relevent data
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write.csv(output[,-2],"Randomized_trials.csv")
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pairs.panels(trials)
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plot(trials,type = 'l')

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