https://github.com/cran/sjPlot
Tip revision: 2faf997c3cf962566c949e74e58889282855ad9f authored by Daniel Luedecke on 10 September 2014, 11:38:24 UTC
version 1.5
version 1.5
Tip revision: 2faf997
sjTabPCA.R
#' @title Show principal component analysis as HTML table
#' @name sjt.pca
#' @references \itemize{
#' \item \url{http://strengejacke.wordpress.com/sjplot-r-package/}
#' \item \url{http://strengejacke.wordpress.com/2014/03/04/beautiful-table-outputs-in-r-part-2-rstats-sjplot/}
#' }
#'
#' @description Performes a principle component analysis on a data frame or matrix and
#' displays the factor solution as HTML table, or saves them as file.
#' \cr \cr In case a data frame is used as
#' parameter, the Cronbach's Alpha value for each factor scale will be calculated,
#' i.e. all variables with the highest loading for a factor are taken for the
#' reliability test. The result is an alpha value for each factor dimension.
#'
#' @seealso \code{\link{sjp.pca}} \cr
#' \code{\link{sjs.reliability}} \cr
#' \code{\link{sjt.itemanalysis}} \cr
#' \code{\link{sjs.cronbach}}
#'
#' @param data A data frame with factors (each columns one variable) that should be used
#' to compute a PCA, or a \code{\link{prcomp}} object.
#' @param numberOfFactors A predefined number of factors to use for the calculating the varimax
#' rotation. By default, this value is \code{NULL} and the amount of factors is
#' calculated according to the Kaiser-criteria. See paramater \code{plotEigenvalues}.
#' @param factorLoadingTolerance Specifies the minimum difference a variable needs to have between
#' factor loadings (components) in order to indicate a clear loading on just one factor and not
#' diffusing over all factors. For instance, a variable with 0.8, 0.82 and 0.84 factor loading
#' on 3 possible factors can not be clearly assigned to just one factor and thus would be removed
#' from the principal component analysis. By default, the minimum difference of loading values
#' between the highest and 2nd highest factor should be 0.1
#' @param file The destination file, which will be in html-format. If no filepath is specified,
#' the file will be saved as temporary file and openend either in the RStudio View pane or
#' in the default web browser.
#' @param varlabels The item labels that are printed in the first column. If no item labels are
#' provided (default), the data frame's column names are used. Item labels must
#' be a string vector, e.g.: \code{varlabels=c("Var 1", "Var 2", "Var 3")}.
#' @param title A table caption. By default, \code{"Principal Component Analysis (with varimax rotation)"}
#' is used as the table's title.
#' @param breakLabelsAt Wordwrap for diagram labels. Determines how many chars of the variable labels are displayed in
#' one line and when a line break is inserted. Default is 20.
#' @param digits The amount of digits used the values inside table cells.
#' Default is 2.
#' @param showCronbachsAlpha If \code{TRUE} (default), the cronbach's alpha value for each factor scale will be calculated,
#' i.e. all variables with the highest loading for a factor are taken for the
#' reliability test. The result is an alpha value for each factor dimension.
#' Only applies when \code{data} is a data frame and no \code{\link{prcomp}} object.
#' @param showMSA If \code{TRUE}, shows an additional column with the measure of sampling adequacy according
#' dor each component.
#' @param showVariance If \code{TRUE}, the proportions of variances for each component as well as cumulative
#' variance are shown in the table footer.
#' @param alternateRowColors If \code{TRUE}, alternating rows are highlighted with a light gray
#' background color.
#' @param stringPov The string for the table row that contains the proportions of variances. By default,
#' \code{"Proportion of Variance"} will be used.
#' @param stringCpov The string for the table row that contains the cumulative variances. By default,
#' \code{"Cumulative Proportion"} will be used.
#' @param encoding The charset encoding used for variable and value labels. Default is \code{"UTF-8"}. Change
#' encoding if specific chars are not properly displayed (e.g.) German umlauts).
#' @param CSS A \code{\link{list}} with user-defined style-sheet-definitions, according to the official CSS syntax (see
#' \url{http://www.w3.org/Style/CSS/}). See return value \code{page.style} for details
#' of all style-sheet-classnames that are used in this function. Parameters for this list need:
#' \enumerate{
#' \item the class-names with \code{"css."}-prefix as parameter name and
#' \item each style-definition must end with a semicolon
#' }
#' You can add style information to the default styles by using a + (plus-sign) as
#' initial character for the parameter attributes. Examples:
#' \itemize{
#' \item \code{css.table='border:2px solid red;'} for a solid 2-pixel table border in red.
#' \item \code{css.summary='font-weight:bold;'} for a bold fontweight in the summary row.
#' \item \code{css.lasttablerow='border-bottom: 1px dotted blue;'} for a blue dotted border of the last table row.
#' \item \code{css.cronbach='+color:green;'} to add green color formatting to the Cronbach's Alpha value.
#' }
#' See further examples below and \url{http://rpubs.com/sjPlot/sjtbasics}.
#' @param useViewer If \code{TRUE}, the function tries to show the HTML table in the IDE's viewer pane. If
#' \code{FALSE} or no viewer available, the HTML table is opened in a web browser.
#' @param no.output If \code{TRUE}, the html-output is neither opened in a browser nor shown in
#' the viewer pane and not even saved to file. This option is useful when the html output
#' should be used in \code{knitr} documents. The html output can be accessed via the return
#' value.
#' @return Invisibly returns a \code{\link{structure}} with
#' \itemize{
#' \item the web page style sheet (\code{page.style}),
#' \item the web page content (\code{page.content}),
#' \item the complete html-output (\code{output.complete}),
#' \item the html-table with inline-css for use with knitr (\code{knitr}),
#' \item the \code{factor.index}, i.e. the column index of each variable with the highest factor loading for each factor and
#' \item the \code{removed.items}, i.e. which variables have been removed because they were outside of the \code{factorLoadingTolerance}'s range.
#' }
#' for further use.
#'
#' @note The HTML tables can either be saved as file and manually opened (specify parameter \code{file}) or
#' they can be saved as temporary files and will be displayed in the RStudio Viewer pane (if working with RStudio)
#' or opened with the default web browser. Displaying resp. opening a temporary file is the
#' default behaviour (i.e. \code{file=NULL}). \cr \cr
#' This PCA uses the \code{\link{prcomp}} function and the \code{\link{varimax}} rotation.
#'
#' @examples
#' # randomly create data frame with 7 items, each consisting of 4 categories
#' likert_4 <- data.frame(sample(1:4, 500, replace=TRUE, prob=c(0.2,0.3,0.1,0.4)),
#' sample(1:4, 500, replace=TRUE, prob=c(0.5,0.25,0.15,0.1)),
#' sample(1:4, 500, replace=TRUE, prob=c(0.4,0.15,0.25,0.2)),
#' sample(1:4, 500, replace=TRUE, prob=c(0.25,0.1,0.4,0.25)),
#' sample(1:4, 500, replace=TRUE, prob=c(0.1,0.4,0.4,0.1)),
#' sample(1:4, 500, replace=TRUE),
#' sample(1:4, 500, replace=TRUE, prob=c(0.35,0.25,0.15,0.25)))
#'
#' # Create variable labels
#' colnames(likert_4) <- c("V1", "V2", "V3", "V4", "V5", "V6", "V7")
#'
#' # show table
#' \dontrun{
#' sjt.pca(likert_4)}
#'
#' # -------------------------------
#' # Data from the EUROFAMCARE sample dataset
#' # -------------------------------
#' data(efc)
#'
#' # retrieve variable and value labels
#' varlabs <- sji.getVariableLabels(efc)
#'
#' # recveive first item of COPE-index scale
#' start <- which(colnames(efc)=="c82cop1")
#' # recveive last item of COPE-index scale
#' end <- which(colnames(efc)=="c90cop9")
#'
#' # create data frame with COPE-index scale
#' df <- as.data.frame(efc[,c(start:end)])
#' colnames(df) <- varlabs[c(start:end)]
#'
#' \dontrun{
#' sjt.pca(df)}
#'
#' # -------------------------------
#' # auto-detection of labels
#' # -------------------------------
#' efc <- sji.setVariableLabels(efc, varlabs)
#' \dontrun{
#' sjt.pca(efc[,c(start:end)])}
#'
#' @importFrom psych KMO
#' @export
sjt.pca <- function (data,
numberOfFactors=NULL,
factorLoadingTolerance=0.1,
file=NULL,
varlabels=NULL,
title="Principal Component Analysis (with varimax rotation)",
breakLabelsAt=40,
digits=2,
showCronbachsAlpha=TRUE,
showMSA=FALSE,
showVariance=FALSE,
alternateRowColors=FALSE,
stringPov="Proportion of Variance",
stringCpov="Cumulative Proportion",
encoding="UTF-8",
CSS=NULL,
useViewer=TRUE,
no.output=FALSE) {
# --------------------------------------------------------
# try to automatically set labels is not passed as parameter
# --------------------------------------------------------
if (is.null(varlabels) && is.data.frame(data)) {
# if yes, iterate each variable
for (i in 1:ncol(data)) {
# retrieve variable name attribute
vn <- autoSetVariableLabels(data[,i])
# if variable has attribute, add to variableLabel list
if (!is.null(vn)) {
varlabels <- c(varlabels, vn)
}
else {
# else break out of loop
varlabels <- NULL
break
}
}
}
# ----------------------------
# check if user has passed a data frame
# or a pca object
# ----------------------------
if (class(data)=="prcomp") {
pcadata <- data
dataframeparam <- FALSE
showMSA <- FALSE
}
else {
pcadata <- prcomp(na.omit(data), retx=TRUE, center=TRUE, scale.=TRUE)
dataframeparam <- TRUE
}
# -------------------------------------
# init header
# -------------------------------------
toWrite <- sprintf("<html>\n<head>\n<meta http-equiv=\"Content-type\" content=\"text/html;charset=%s\">\n", encoding)
# -------------------------------------
# init style sheet and tags used for css-definitions
# we can use these variables for string-replacement
# later for return value
# -------------------------------------
tag.table <- "table"
tag.caption <- "caption"
tag.thead <- "thead"
tag.tdata <- "tdata"
tag.centeralign <- "centeralign"
tag.cronbach <- "cronbach"
tag.msa <- "msa"
tag.pov <- "pov"
tag.cpov <- "cpov"
tag.kmo <- "kmo"
tag.arc <- "arc"
tag.minval <- "minval"
tag.removable <- "removable"
tag.firsttablerow <- "firsttablerow"
tag.firsttablecol <- "firsttablecol"
css.table <- "border-collapse:collapse; border:none;"
css.caption <- "font-weight: bold; text-align:left;"
css.thead <- "border-top:double black; padding:0.2cm;"
css.tdata <- "padding:0.2cm;"
css.centeralign <- "text-align:center;"
css.cronbach <- "font-style:italic;"
css.msa <- "font-style:italic; color:#666666;"
css.kmo <- "font-style:italic; border-bottom:double;"
css.pov <- "font-style:italic; border-top:1px solid;"
css.cpov <- "font-style:italic;"
css.minval <- "color:#cccccc;"
css.arc <- "background-color:#eaeaea;"
css.removable <- "background-color:#eacccc;"
css.firsttablerow <- "border-top:1px solid black;"
css.firsttablecol <- ""
if (!showMSA && !showCronbachsAlpha) css.cpov <- sprintf("%s border-bottom:double;", css.cpov)
if (!showMSA && showCronbachsAlpha) css.cronbach <- sprintf("%s border-bottom:double;", css.cronbach)
if (!showVariance && showCronbachsAlpha) css.cronbach <- sprintf("%s border-top:1px solid;", css.cronbach)
if (!showVariance && !showCronbachsAlpha) css.kmo <- sprintf("%s border-top:1px solid;",css.kmo)
if (!showVariance && !showCronbachsAlpha && !showMSA) css.table <- sprintf("%s border-bottom:double;", css.table)
# ------------------------
# check user defined style sheets
# ------------------------
if (!is.null(CSS)) {
if (!is.null(CSS[['css.table']])) css.table <- ifelse(substring(CSS[['css.table']],1,1)=='+', paste0(css.table, substring(CSS[['css.table']],2)), CSS[['css.table']])
if (!is.null(CSS[['css.thead']])) css.thead <- ifelse(substring(CSS[['css.thead']],1,1)=='+', paste0(css.thead, substring(CSS[['css.thead']],2)), CSS[['css.thead']])
if (!is.null(CSS[['css.tdata']])) css.tdata <- ifelse(substring(CSS[['css.tdata']],1,1)=='+', paste0(css.tdata, substring(CSS[['css.tdata']],2)), CSS[['css.tdata']])
if (!is.null(CSS[['css.caption']])) css.caption <- ifelse(substring(CSS[['css.caption']],1,1)=='+', paste0(css.caption, substring(CSS[['css.caption']],2)), CSS[['css.caption']])
if (!is.null(CSS[['css.centeralign']])) css.centeralign <- ifelse(substring(CSS[['css.centeralign']],1,1)=='+', paste0(css.centeralign, substring(CSS[['css.centeralign']],2)), CSS[['css.centeralign']])
if (!is.null(CSS[['css.arc']])) css.arc <- ifelse(substring(CSS[['css.arc']],1,1)=='+', paste0(css.arc, substring(CSS[['css.arc']],2)), CSS[['css.arc']])
if (!is.null(CSS[['css.firsttablerow']])) css.firsttablerow <- ifelse(substring(CSS[['css.firsttablerow']],1,1)=='+', paste0(css.firsttablerow, substring(CSS[['css.firsttablerow']],2)), CSS[['css.firsttablerow']])
if (!is.null(CSS[['css.firsttablecol']])) css.firsttablecol <- ifelse(substring(CSS[['css.firsttablecol']],1,1)=='+', paste0(css.firsttablecol, substring(CSS[['css.firsttablecol']],2)), CSS[['css.firsttablecol']])
if (!is.null(CSS[['css.cronbach']])) css.cronbach <- ifelse(substring(CSS[['css.cronbach']],1,1)=='+', paste0(css.cronbach, substring(CSS[['css.cronbach']],2)), CSS[['css.cronbach']])
if (!is.null(CSS[['css.msa']])) css.msa <- ifelse(substring(CSS[['css.msa']],1,1)=='+', paste0(css.msa, substring(CSS[['css.msa']],2)), CSS[['css.msa']])
if (!is.null(CSS[['css.kmo']])) css.kmo <- ifelse(substring(CSS[['css.kmo']],1,1)=='+', paste0(css.kmo, substring(CSS[['css.kmo']],2)), CSS[['css.kmo']])
if (!is.null(CSS[['css.pov']])) css.pov <- ifelse(substring(CSS[['css.pov']],1,1)=='+', paste0(css.pov, substring(CSS[['css.pov']],2)), CSS[['css.pov']])
if (!is.null(CSS[['css.cpov']])) css.cpov <- ifelse(substring(CSS[['css.cpov']],1,1)=='+', paste0(css.cpov, substring(CSS[['css.cpov']],2)), CSS[['css.cpov']])
if (!is.null(CSS[['css.minval']])) css.minval <- ifelse(substring(CSS[['css.minval']],1,1)=='+', paste0(css.minval, substring(CSS[['css.minval']],2)), CSS[['css.minval']])
if (!is.null(CSS[['css.removable']])) css.removable <- ifelse(substring(CSS[['css.removable']],1,1)=='+', paste0(css.removable, substring(CSS[['css.removable']],2)), CSS[['css.removable']])
}
# ------------------------
# set page style
# ------------------------
page.style <- sprintf("<style>%s { %s }\n.%s { %s }\n.%s { %s }\n.%s { %s }\n.%s { %s }\n.%s { %s }\n.%s { %s }\n.%s { %s }\n.%s { %s }\n.%s { %s }\n.%s { %s }\n%s { %s }\n.%s { %s }\n.%s { %s }\n.%s { %s }\n</style>",
tag.table, css.table, tag.thead, css.thead, tag.tdata, css.tdata,
tag.cronbach, css.cronbach, tag.minval, css.minval,
tag.removable, css.removable, tag.firsttablerow, css.firsttablerow,
tag.firsttablecol, css.firsttablecol, tag.centeralign, css.centeralign,
tag.msa, css.msa, tag.kmo, css.kmo, tag.caption, css.caption,
tag.pov, css.pov, tag.cpov, css.cpov, tag.arc, css.arc)
# ------------------------
# start content
# ------------------------
toWrite <- paste0(toWrite, page.style)
toWrite = paste(toWrite, "\n</head>\n<body>", "\n")
# ----------------------------
# calculate eigenvalues
# ----------------------------
pcadata.eigenval <- pcadata$sdev^2
# ----------------------------
# retrieve best amount of factors according
# to Kaiser-critearia, i.e. factors with eigen value > 1
# ----------------------------
pcadata.kaiser <- which(pcadata.eigenval<1)[1]-1
# --------------------------------------------------------
# varimax rotation, retrieve factor loadings
# --------------------------------------------------------
# check for predefined number of factors
if (!is.null(numberOfFactors) && is.numeric(numberOfFactors)) {
pcadata.kaiser <- numberOfFactors
}
pcadata.varim = varimaxrota(pcadata, pcadata.kaiser)
# create data frame with factor loadings
df <- as.data.frame(pcadata.varim$loadings[,1:ncol(pcadata.varim$loadings)])
# ----------------------------
# check if user defined labels have been supplied
# if not, use variable names from data frame
# ----------------------------
if (is.null(varlabels)) {
varlabels <- row.names(df)
}
# ----------------------------
# Prepare length of labels
# ----------------------------
if (!is.null(varlabels)) {
# wrap long variable labels
varlabels <- sju.wordwrap(varlabels, breakLabelsAt, "<br>")
}
# --------------------------------------------------------
# this function checks which items have unclear factor loadings,
# i.e. which items do not strongly load on a single factor but
# may load almost equally on several factors
# --------------------------------------------------------
getRemovableItems <- function(dataframe) {
# clear vector
removers <- c()
# iterate each row of the data frame. each row represents
# one item with its factor loadings
for (i in 1:nrow(dataframe)) {
# get factor loadings for each item
rowval <- as.numeric(abs(df[i,]))
# retrieve highest loading
maxload <- max(rowval)
# retrieve 2. highest loading
max2load <- sort(rowval, TRUE)[2]
# check difference between both
if (abs(maxload-max2load)<factorLoadingTolerance) {
# if difference is below the tolerance,
# remeber row-ID so we can remove that items
# for further PCA with updated data frame
removers <- c(removers, i)
}
}
# return a vector with index numbers indicating which items
# have unclear loadings
return (removers)
}
# --------------------------------------------------------
# this function retrieves a list with the column index ("factor" index)
# where each case of the data frame has its highedt factor loading.
# So we know to which "group" (factor dimension) each case of the
# data frame belongs to according to the pca results
# --------------------------------------------------------
getItemLoadings <- function(dataframe) {
# clear vector
itemloading <- c()
# iterate each row of the data frame. each row represents
# one item with its factor loadings
for (i in 1:nrow(dataframe)) {
# get factor loadings for each item
rowval <- abs(df[i,])
# retrieve highest loading and remeber that column
itemloading <- c(itemloading, which(rowval==max(rowval)))
}
# return a vector with index numbers indicating which items
# loads the highest on which factor
return (itemloading)
}
# --------------------------------------------------------
# this function calculates the cronbach's alpha value for
# each factor scale, i.e. all variables with the highest loading
# for a factor are taken for the reliability test. The result is
# an alpha value for each factor dimension
# --------------------------------------------------------
getCronbach <- function(dataframe, itemloadings) {
# clear vector
cbv <- c()
# iterate all highest factor loadings of items
for (n in 1:length(unique(itemloadings))) {
# calculate cronbach's alpha for those cases that all have the
# highest loading on the same factor
cbv <- c(cbv, sjs.cronbach(na.omit(dataframe[,which(itemloadings==n)])))
}
# cbv now contains the factor numbers and the related alpha values
# for each "factor dimension scale"
return(cbv)
}
# ----------------------------------
# Cronbach's Alpha can only be calculated when having a data frame
# with each component / variable as column
# ----------------------------------
if (dataframeparam) {
# get alpha values
alphaValues <- getCronbach(data, getItemLoadings(df))
}
else {
cat("\nCronbach's Alpha can only be calculated when having a data frame with each component / variable as column\n")
alphaValues <- NULL
showCronbachsAlpha <- FALSE
}
# -------------------------------------
# retrieve those items that have unclear factor loadings, i.e.
# which almost load equally on several factors. The tolerance
# that indicates which difference between factor loadings is
# considered as "equally" is defined via factorLoadingTolerance
# -------------------------------------
removableItems <- getRemovableItems(df)
# -------------------------------------
# retrieve kmo and msa for data set
# -------------------------------------
kmo <- NULL
if (showMSA) kmo <- KMO(data)
# -------------------------------------
# variance
# -------------------------------------
pov <- cpov <- NULL
if (showVariance) {
pov <- summary(pcadata)$importance[2,1:pcadata.kaiser]
cpov <- summary(pcadata)$importance[3,1:pcadata.kaiser]
}
# -------------------------------------
# convert data frame, add label names
# -------------------------------------
maxdf <- apply(df,1,function(x) max(abs(x)))
# -------------------------------------
# start table tag
# -------------------------------------
page.content <- "<table>\n"
# -------------------------------------
# table caption, variable label
# -------------------------------------
if (!is.null(title)) page.content <- paste0(page.content, sprintf(" <caption>%s</caption>\n", title))
# -------------------------------------
# header row
# -------------------------------------
# write tr-tag
page.content <- paste0(page.content, " <tr>\n")
# first column
page.content <- paste0(page.content, " <th class=\"thead\"> </th>\n")
# iterate columns
for (i in 1:ncol(df)) {
page.content <- paste0(page.content, sprintf(" <th class=\"thead\">Component %i</th>\n", i))
}
# check if msa column should be shown
if (showMSA) page.content <- paste0(page.content, " <th class=\"thead msa\">MSA</th>\n")
# close table row
page.content <- paste0(page.content, " </tr>\n")
# -------------------------------------
# data rows
# -------------------------------------
# iterate all rows of df
for (i in 1:nrow(df)) {
# start table row
rowcss <- ""
# check for removable items in first row
if (i %in% removableItems && i==1) rowcss <- " firsttablerow removable"
# check for removable items in other rows
if (i %in% removableItems && i!=1) rowcss <- " removable"
# check for non-removable items in first row
if (is.na(match(i, removableItems)) && i==1) rowcss <- " firsttablerow"
# default row string for alternative row colors
arcstring <- ""
# if we have alternating row colors, set css
if (alternateRowColors) arcstring <- ifelse(i %% 2 ==0, " arc", "")
# write tr-tag with class-attributes
page.content <- paste0(page.content, " <tr>\n")
# print first table cell
page.content <- paste0(page.content, sprintf(" <td class=\"firsttablecol%s%s\">%s</td>\n", arcstring, rowcss, varlabels[i]))
# iterate all columns
for (j in 1:ncol(df)) {
# start table column
colcss <- sprintf(" class=\"tdata centeralign%s%s\"", arcstring, rowcss)
if (maxdf[[i]]!=max(abs(df[i,j]))) colcss <- sprintf(" class=\"tdata centeralign minval%s%s\"", arcstring, rowcss)
page.content <- paste0(page.content, sprintf(" <td%s>%.*f</td>\n", colcss, digits, df[i,j]))
}
# check if msa column should be shown
if (showMSA) page.content <- paste0(page.content, sprintf(" <td class=\"tdata msa centeralign%s%s\">%.*f</td>\n", arcstring, rowcss, digits, kmo$MSAi[[i]]))
# close row
page.content <- paste0(page.content, " </tr>\n")
}
# -------------------------------------
# variance
# -------------------------------------
if (showVariance) {
# write tr-tag with class-attributes
page.content <- paste0(page.content, " <tr>\n")
# first column
page.content <- paste0(page.content, sprintf(" <td class=\"tdata pov\">%s</td>\n", stringPov))
# iterate alpha-values
for (i in 1:length(pov)) {
page.content <- paste0(page.content, sprintf(" <td class=\"tdata centeralign pov\">%.*f %%</td>\n", digits, 100*pov[i]))
}
# check if msa column should be shown
if (showMSA) page.content <- paste0(page.content, " <td class=\"tdata centeralign pov\"></td>\n")
page.content <- paste0(page.content, " </tr>\n <tr>\n")
# first column
page.content <- paste0(page.content, sprintf(" <td class=\"tdata cpov\">%s</td>\n", stringCpov))
# iterate alpha-values
for (i in 1:length(pov)) {
page.content <- paste0(page.content, sprintf(" <td class=\"tdata centeralign cpov\">%.*f %%</td>\n", digits, 100*cpov[i]))
}
# check if msa column should be shown
if (showMSA) page.content <- paste0(page.content, " <td class=\"tdata centeralign cpov\"></td>\n")
page.content <- paste0(page.content, " </tr>\n")
}
# -------------------------------------
# cronbach's alpha
# -------------------------------------
if (showCronbachsAlpha && !is.null(alphaValues)) {
# write tr-tag with class-attributes
page.content <- paste0(page.content, " <tr>\n")
# first column
page.content <- paste0(page.content, " <td class=\"tdata cronbach\">Cronbach's α</td>\n")
# iterate alpha-values
for (i in 1:length(alphaValues)) {
page.content <- paste0(page.content, sprintf(" <td class=\"tdata centeralign cronbach\">%.*f</td>\n", digits, alphaValues[i]))
}
# check if msa column should be shown
if (showMSA) page.content <- paste0(page.content, " <td class=\"tdata centeralign cronbach\"></td>\n")
page.content <- paste0(page.content, " </tr>\n")
}
# -------------------------------------
# Kaiser-Meyer-Olkin-Kriterium
# -------------------------------------
if (showMSA) {
# write tr-tag with class-attributes
page.content <- paste0(page.content, " <tr>\n")
page.content <- paste0(page.content, " <td class=\"tdata kmo\">Kaiser-Meyer-Olkin</td>\n")
page.content <- paste0(page.content, sprintf(" <td class=\"tdata centeralign kmo\" colspan=\"%i\"></td>\n", ncol(df)))
page.content <- paste0(page.content, sprintf(" <td class=\"tdata centeralign kmo\">%.*f</td>\n", digits, kmo$MSA))
page.content <- paste0(page.content, " </tr>\n")
}
# -------------------------------------
# finish table
# -------------------------------------
page.content <- paste(page.content, "\n</table>")
# -------------------------------------
# finish html page
# -------------------------------------
toWrite <- paste(toWrite, page.content, "\n")
toWrite <- paste0(toWrite, "</body></html>")
# -------------------------------------
# create list with factor loadings that indicate
# on which column inside the data frame the highest
# loading is
# -------------------------------------
factorindex <- c()
for (i in 1:nrow(df)) {
factorindex <- c(factorindex, which.max(abs(df[i,])))
}
# -------------------------------------
# replace class attributes with inline style,
# useful for knitr
# -------------------------------------
# copy page content
# -------------------------------------
knitr <- page.content
# -------------------------------------
# set style attributes for main table tags
# -------------------------------------
knitr <- gsub("class=", "style=", knitr)
knitr <- gsub("<table", sprintf("<table style=\"%s\"", css.table), knitr)
knitr <- gsub("<caption", sprintf("<caption style=\"%s\"", css.caption), knitr)
# -------------------------------------
# replace class-attributes with inline-style-definitions
# -------------------------------------
knitr <- gsub(tag.tdata, css.tdata, knitr)
knitr <- gsub(tag.thead, css.thead, knitr)
knitr <- gsub(tag.centeralign, css.centeralign, knitr)
knitr <- gsub(tag.cronbach, css.cronbach, knitr)
knitr <- gsub(tag.msa, css.msa, knitr)
knitr <- gsub(tag.pov, css.pov, knitr)
knitr <- gsub(tag.arc, css.arc, knitr)
knitr <- gsub(tag.cpov, css.cpov, knitr)
knitr <- gsub(tag.kmo, css.kmo, knitr)
knitr <- gsub(tag.minval, css.minval, knitr)
knitr <- gsub(tag.removable, css.removable, knitr)
knitr <- gsub(tag.firsttablerow, css.firsttablerow, knitr)
knitr <- gsub(tag.firsttablecol, css.firsttablecol, knitr)
# -------------------------------------
# check if html-content should be outputted
# -------------------------------------
if (!no.output) {
# -------------------------------------
# check if we have filename specified
# -------------------------------------
if (!is.null(file)) {
# write file
write(knitr, file=file)
}
# -------------------------------------
# else open in viewer pane
# -------------------------------------
else {
# else create and browse temporary file
htmlFile <- tempfile(fileext=".html")
write(toWrite, file=htmlFile)
# check whether we have RStudio Viewer
viewer <- getOption("viewer")
if (useViewer && !is.null(viewer)) {
viewer(htmlFile)
}
else {
utils::browseURL(htmlFile)
}
# delete temp file
# unlink(htmlFile)
}
}
# -------------------------------------
# return results
# -------------------------------------
invisible (structure(class = "sjtpca",
list(page.style = page.style,
page.content = page.content,
output.complete = toWrite,
knitr = knitr,
factor.index = factorindex,
removed.items = removableItems)))
}