Correlation

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Option:

Note: Input values must be separated by tabs. Copy and paste from Excel/Numbers.


                
                

Basic statistics


                

Box plots with individual data points


Correlation


                

95% confidence interval (CI)


                

Scatter plot matrices



R session info

              
Note

This web application is developed with Shiny.


List of Packages Used
library(shiny)
library(shinyAce)
library(psych)
library(beeswarm)

Code

Source code for this application is based on "The handbook of Research in Foreign Language Learning and Teaching" (Takeuchi & Mizumoto, 2012).

The code for this web application is available at GitHub.

If you want to run this code on your computer (in a local R session), run the code below:
library(shiny)
runGitHub("cor","mizumot")


Citation in Publications

Mizumoto, A. (2015). Langtest (Version 1.0) [Web application]. Retrieved from http://langtest.jp


Article

Mizumoto, A., & Plonsky, L. (2015). R as a lingua franca: Advantages of using R for quantitative research in applied linguistics. Applied Linguistics, Advance online publication. doi:10.1093/applin/amv025


Recommended

To learn more about R, I suggest this excellent and free e-book (pdf), A Guide to Doing Statistics in Second Language Research Using R, written by Dr. Jenifer Larson-Hall.

Also, if you are a cool Mac user and want to use R with GUI, MacR is defenitely the way to go!


Author

Atsushi MIZUMOTO, Ph.D.
Associate Professor of Applied Linguistics
Faculty of Foreign Language Studies /
Graduate School of Foreign Language Education and Research,
Kansai University, Osaka, Japan



Code for "Correlation"
by Atsushi Mizumoto

show with app
library(shiny)
library(shinyAce)
library(psych)
library(beeswarm)



shinyServer(function(input, output) {


    bs <- reactive({
        if (input$colname == 0) {
            x <- read.csv(text=input$text, header=FALSE, sep="", na.strings=c("","NA","."))
            x <- as.matrix(x)
            describe(x)[2:13]
        } else {
            x <- read.csv(text=input$text, sep="", na.strings=c("","NA","."))
            describe(x)[2:13]
        }
    })

    output$textarea.out <- renderPrint({
        bs()
    })



    makeboxPlot <- function(){
        if (input$colname == 0) {
            dat <- read.csv(text=input$text, header=FALSE, sep="", na.strings=c("","NA","."))
        } else {
            dat <- read.csv(text=input$text, sep="", na.strings=c("","NA","."))
        }

        boxplot(dat, las=1, xlab= "Means and +/-1 SDs are displayed in red.")
        beeswarm(dat, col = 4, pch = 16, vert = TRUE,  add = TRUE)
        for (i in 1:ncol(dat)) {
            pts <- 0.2 + i
            mns <- mean(dat[,i], na.rm=TRUE)
            sds <- sd(dat[,i], na.rm=TRUE)

            points(pts, mns, pch = 18, col = "red", cex = 2)
            arrows(pts, mns, pts, mns + sds, length = 0.1, angle = 45, col = "red")
            arrows(pts, mns, pts, mns - sds, length = 0.1, angle = 45, col = "red")
        }
    }

    output$boxPlot <- renderPlot({
        print(makeboxPlot())
    })



    correl <- reactive({

        if (input$colname == 0) {
            # x <- read.table(text=input$text, sep="", na.strings=c("","NA","."))
            x <- read.table(text=input$text, sep="\t")
            x <- as.matrix(x)

            type <- switch(input$method,
                           Pearson = "pearson",
                           Spearman = "spearman",
                           Kendall = "kendall")

            round(cor(cbind(x), method = type, use = "pairwise.complete.obs"),3)

        } else {
            # x <- read.csv(text=input$text, sep="", na.strings=c("","NA","."))
            x <- read.csv(text=input$text, sep="\t")

            type <- switch(input$method,
                           Pearson = "pearson",
                           Spearman = "spearman",
                           Kendall = "kendall")

            round(cor(cbind(x), method = type, use = "pairwise.complete.obs"),3)
        }
    })

    output$correl.out <- renderPrint({
        correl()
    })



    ci <- reactive({

        if (input$colname == 0) {
            #x <- read.csv(text=input$text, header=FALSE, sep="", na.strings=c("","NA","."))
          x <- read.csv(text=input$text, header=FALSE, sep="\t")

        } else {

        # x <- read.csv(text=input$text, sep="", na.strings=c("","NA","."))
          x <- read.csv(text=input$text, sep="\t")


        }

           type <- switch(input$method,
                        Pearson = "pearson",
                        Spearman = "spearman",
                        Kendall = "kendall")

           ci.all <- function(x) {

                for (i in 1:length(x)) {
                    for (j in 1:length(x)) {
                        if (i >= j) {
                            next
                        } else {

                            r <- cor(x[,i], x[,j], method = type, use = "complete")
                            n <- length(x[,1])
                            pvl <- cor.test(x[,i], x[,j], method = type)
                            
                            if (input$method == "Kendall") {
                                # [Kendall CI] http://www.stat.umn.edu/geyer/5601/examp/corr.html
                                conf.level <- 0.95
                                signs <- sign(outer(x[,i], x[,i], "-") * outer(x[,j], x[,j], "-"))
                                tau <- mean(signs[lower.tri(signs)])
                                cvec <- apply(signs, 1, sum)
                                nn <- length(cvec)
                                sigsq <- (2 / (nn * (nn - 1))) *
                                    (((2 * (nn - 2)) / (nn * (nn - 1))) * var(cvec)
                                    + 1 - tau^2)
                                zcrit <- qnorm((1 + conf.level) / 2)
                                ci <- tau + c(-1, 1) * zcrit * sqrt(sigsq)

                            } else {
                                ci <- round(r.con(r, n), 3)
                                # [Spearman CI] http://www.statsdirect.com/help/default.htm#nonparametric_methods/spearman.htm
                            }
                            
                                if (input$method == "Pearson") {
                                    cortype <- c("Pearson's r =")
                                } else if (input$method == "Spearman") {
                                    cortype <- c("Spearman's ρ =")
                                } else {
                                    cortype <- c("Kendall's τ =")
                                }
                            
                            cat("----------", "\n", 
                            "Correlation between", colnames(x)[i], "&", colnames(x)[j], ":", "\n",
                            cortype, round(r, 3), "\n",
                            "95% CI [lower, upper] =", round(ci, 3), "\n",
                            "p-value =", round(pvl$p.value, 3), "\n",
                            "\n")
                        }
                    }
                }
            }

            ci.all(x)

    })

    output$ci.out <- renderPrint({
        ci()
    })



    makecorPlot <- function(){
        if (input$colname == 0) {
            #x <- read.table(text=input$text, sep="", na.strings=c("","NA","."))
            x <- read.table(text=input$text, sep="\t")
            x <- as.matrix(x)

            type <- switch(input$method,
                        Pearson = "pearson",
                        Spearman = "spearman",
                        Kendall = "kendall")

            pairs.panels(x, method = type)

        } else {
            # x <- read.csv(text=input$text, sep="", na.strings=c("","NA","."))
            x <- read.csv(text=input$text, sep="\t")

            type <- switch(input$method,
                        Pearson = "pearson",
                        Spearman = "spearman",
                        Kendall = "kendall")

            pairs.panels(x, method = type)
        }
    }

    output$corPlot <- renderPlot({
        print(makecorPlot())
    })



    info <- reactive({
        info1 <- paste("This analysis was conducted with ", strsplit(R.version$version.string, " \\(")[[1]][1], ".", sep = "")
        info2 <- paste("It was executed on ", date(), ".", sep = "")
        cat(sprintf(info1), "\n")
        cat(sprintf(info2), "\n")
    })

    output$info.out <- renderPrint({
        info()
    })


})
library(shiny)
library(shinyAce)



shinyUI(bootstrapPage(

    headerPanel("Correlation"),

########## Adding loading message #########

tags$head(tags$style(type="text/css", "
#loadmessage {
position: fixed;
top: 0px;
left: 0px;
width: 100%;
padding: 10px 0px 10px 0px;
text-align: center;
font-weight: bold;
font-size: 100%;
color: #000000;
background-color: #CCFF66;
z-index: 105;
}
")),

conditionalPanel(condition="$('html').hasClass('shiny-busy')",
tags$div("Loading...",id="loadmessage")),

########## Added up untill here ##########

    mainPanel(
        tabsetPanel(

        tabPanel("Main",

            strong('Option:'),

            checkboxInput("colname", label = strong("The data includes variable names in the first row."), value = T),

            # br(),

            p('Note: Input values must be separated by tabs. Copy and paste from Excel/Numbers.'),

            # p(HTML("<b><div style='background-color:#FADDF2;border:1px solid black;'>Missing values should be indicated by a period (.) or NA.</div></b>")),

            aceEditor("text", value="Test.A\tTest.B\n67\t70\n56\t68\n55\t66\n89\t77\n90\t100\n92\t60\n44\t55\n36\t44\n88\t76\n47\t55\n44\t45\n46\t88\n90\t88\n88\t78\n77\t89\n21\t33\n78\t87\n80\t67\n66\t87\n44\t57",
                mode="r", theme="terminal"),

            br(),

            h3("Basic statistics"),
            verbatimTextOutput("textarea.out"),

            br(),

            h3("Box plots with individual data points"),

            plotOutput("boxPlot", width="80%"),

            br(),

            h3("Correlation"),

            radioButtons("method", "Check the type of correlation coefficients:",
                        list("Pearson product-moment correlation coefficient" = "Pearson",
                             "Spearman's rank correlation coefficient (Spearman's rho)" = "Spearman",
                             "Kendall tau rank correlation coefficient (Kendall's tau)" = "Kendall")),

            verbatimTextOutput("correl.out"),

            br(),

            h4("95% confidence interval (CI)"),
            verbatimTextOutput("ci.out"),

            br(),

            h3("Scatter plot matrices"),

            plotOutput("corPlot"),

            br(),
            br(),

            strong('R session info'),
            verbatimTextOutput("info.out")

            ),


        tabPanel("About",

            strong('Note'),
            p('This web application is developed with',
            a("Shiny.", href="http://www.rstudio.com/shiny/", target="_blank"),
            ''),

            br(),

            strong('List of Packages Used'), br(),
            code('library(shiny)'),br(),
            code('library(shinyAce)'),br(),
            code('library(psych)'),br(),
            code('library(beeswarm)'),br(),

            br(),

            strong('Code'),
            p('Source code for this application is based on',
            a('"The handbook of Research in Foreign Language Learning and Teaching" (Takeuchi & Mizumoto, 2012).', href='http://mizumot.com/handbook/', target="_blank")),

            p('The code for this web application is available at',
            a('GitHub.', href='https://github.com/mizumot/cor', target="_blank")),

            p('If you want to run this code on your computer (in a local R session), run the code below:',
            br(),
            code('library(shiny)'),br(),
            code('runGitHub("cor","mizumot")')
            ),

            br(),

            strong('Citation in Publications'),
            p('Mizumoto, A. (2015). Langtest (Version 1.0) [Web application]. Retrieved from http://langtest.jp'),

            br(),

            strong('Article'),
            p('Mizumoto, A., & Plonsky, L. (2015).', a("R as a lingua franca: Advantages of using R for quantitative research in applied linguistics.", href='http://applij.oxfordjournals.org/content/early/2015/06/24/applin.amv025.abstract', target="_blank"), em('Applied Linguistics,'), 'Advance online publication. doi:10.1093/applin/amv025'),

            br(),

            strong('Recommended'),
            p('To learn more about R, I suggest this excellent and free e-book (pdf),',
            a("A Guide to Doing Statistics in Second Language Research Using R,", href="http://cw.routledge.com/textbooks/9780805861853/guide-to-R.asp", target="_blank"),
            'written by Dr. Jenifer Larson-Hall.'),

            p('Also, if you are a cool Mac user and want to use R with GUI,',
            a("MacR", href="http://www.urano-ken.com/blog/2013/02/25/installing-and-using-macr/", target="_blank"),
            'is defenitely the way to go!'),

            br(),

            strong('Author'),
            p(a("Atsushi MIZUMOTO,", href="http://mizumot.com", target="_blank"),' Ph.D.',br(),
            'Associate Professor of Applied Linguistics',br(),
            'Faculty of Foreign Language Studies /',br(),
            'Graduate School of Foreign Language Education and Research,',br(),
            'Kansai University, Osaka, Japan'),

            br(),

            a(img(src="http://i.creativecommons.org/p/mark/1.0/80x15.png"), target="_blank", href="http://creativecommons.org/publicdomain/mark/1.0/"),

            p(br())

            )

))
))
Code license: GPL-3