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|
#' @title Summary of principal component analysis as HTML table
#' @name tab_pca
#'
#' @description Performes a principle component analysis on a data frame or matrix
#' (with varimax or oblimin rotation) 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.
#'
#' @param data A data frame that should be used to compute a PCA, or a \code{\link{prcomp}} object.
#' @param rotation Rotation of the factor loadings. May be one of
#' \code{"varimax", "quartimax", "promax", "oblimin", "simplimax", "cluster"}
#' or \code{"none"}.
#' @param nmbr.fctr Number of factors used for calculating the rotation. By
#' default, this value is \code{NULL} and the amount of factors is
#' calculated according to the Kaiser-criteria.
#' @param fctr.load.tlrn 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 show.cronb Logical, 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.
#' @param show.msa Logical, if \code{TRUE}, shows an additional column with the measure of sampling adequacy according
#' dor each component.
#' @param show.var Logical, if \code{TRUE}, the proportions of variances for each component as well as cumulative
#' variance are shown in the table footer.
#' @param string.pov String for the table row that contains the proportions of variances. By default,
#' \emph{"Proportion of Variance"} will be used.
#' @param string.cpov String for the table row that contains the cumulative variances. By default,
#' \emph{"Cumulative Proportion"} will be used.
#'
#' @inheritParams tab_model
#' @inheritParams view_df
#' @inheritParams tab_df
#' @inheritParams tab_xtab
#' @inheritParams plot_grpfrq
#' @inheritParams tab_corr
#'
#' @return Invisibly returns
#' \itemize{
#' \item the web page style sheet (\code{page.style}),
#' \item the web page content (\code{page.content}),
#' \item the complete html-output (\code{page.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{fctr.load.tlrn}'s range.
#' }
#' for further use.
#'
#' @examples
#' \dontrun{
#' # Data from the EUROFAMCARE sample dataset
#' library(sjmisc)
#' data(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")
#' # auto-detection of labels
#' if (interactive()) {
#' tab_pca(efc[, start:end])
#' }}
#' @importFrom stats prcomp
#' @importFrom performance cronbachs_alpha
#' @export
tab_pca <- function(data,
rotation = c("varimax", "quartimax", "promax", "oblimin", "simplimax", "cluster", "none"),
nmbr.fctr = NULL,
fctr.load.tlrn = 0.1,
title = "Principal Component Analysis",
var.labels = NULL,
wrap.labels = 40,
show.cronb = TRUE,
show.msa = FALSE,
show.var = FALSE,
alternate.rows = FALSE,
digits = 2,
string.pov = "Proportion of Variance",
string.cpov = "Cumulative Proportion",
CSS = NULL,
encoding = NULL,
file = NULL,
use.viewer = TRUE,
remove.spaces = TRUE) {
# -------------------------------------
# check encoding
# -------------------------------------
encoding <- get.encoding(encoding, data)
rotation <- match.arg(rotation)
# --------------------------------------------------------
# try to automatically set labels is not passed as parameter
# --------------------------------------------------------
if (is.null(var.labels) && is.data.frame(data)) {
var.labels <- sjlabelled::get_label(data, def.value = colnames(data))
}
if (!requireNamespace("psych", quietly = TRUE)) {
stop("Package 'psych' required for this function to work. Please install it.", call. = FALSE)
}
# ----------------------------
# check if user has passed a data frame
# or a pca object
# ----------------------------
if (inherits(data, "prcomp")) {
pcadata <- data
dataframeparam <- FALSE
show.msa <- FALSE
} else {
pcadata <- stats::prcomp(
stats::na.omit(data),
retx = TRUE,
center = TRUE,
scale. = TRUE
)
dataframeparam <- TRUE
}
# -------------------------------------
# init header
# -------------------------------------
toWrite <- table.header <- 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.rightalign <- "rightalign"
tag.cronbach <- "cronbach"
tag.msa <- "msa"
tag.pov <- "pov"
tag.cpov <- "cpov"
tag.rotate <- "rotate"
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.rightalign <- "text-align:right;"
css.cronbach <- "font-style:italic;"
css.msa <- "font-style:italic; color:#666666;"
css.kmo <- "font-style:italic; border-bottom:double;"
css.rotate <- "font-style:italic; font-size:0.9em;"
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 (!show.msa && !show.cronb) css.cpov <- sprintf("%s border-bottom:double;", css.cpov)
if (!show.msa && show.cronb) css.cronbach <- sprintf("%s border-bottom:double;", css.cronbach)
if (!show.var && show.cronb) css.cronbach <- sprintf("%s border-top:1px solid;", css.cronbach)
if (!show.var && !show.cronb) css.kmo <- sprintf("%s border-top:1px solid;",css.kmo)
if (!show.var && !show.cronb && !show.msa) 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.rightalign']])) css.rightalign <- ifelse(substring(CSS[['css.rightalign']], 1, 1) == '+', paste0(css.rightalign, substring(CSS[['css.rightalign']], 2)), CSS[['css.rightalign']])
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.rotate']])) css.rotate <- ifelse(substring(CSS[['css.rotate']], 1, 1) == '+', paste0(css.rotate, substring(CSS[['css.rotate']], 2)), CSS[['css.rotate']])
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>\nhtml, body { background-color: white; }\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.%s { %s }\n.%s { %s }\n.%s { %s }\n</style>",
tag.table, css.table, tag.caption, css.caption, 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.rightalign, css.rightalign, tag.rotate, css.rotate,
tag.msa, css.msa, tag.kmo, css.kmo, 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$sdev^2
# ----------------------------
# retrieve best amount of factors according
# to Kaiser-critearia, i.e. factors with eigen value > 1
# ----------------------------
pcadata.kaiser <- which(pcadata.eigenval < 1)[1] - 1
# --------------------------------------------------------
# varimax rotation, retrieve factor loadings
# --------------------------------------------------------
# check for predefined number of factors
if (!is.null(nmbr.fctr) && is.numeric(nmbr.fctr)) pcadata.kaiser <- nmbr.fctr
if (pcadata.kaiser < 2) {
stop("Only one principal component extracted. Can't rotate loading matrices. You may use `nmbr.fctr` to extract more than one component.", call. = F)
}
rotation <- match.arg(rotation)
# rotate matrix
if (rotation == "varimax")
pcadata.rotate <- varimaxrota(pcadata, pcadata.kaiser)
else
pcadata.rotate <- psych::principal(r = data, nfactors = pcadata.kaiser, rotate = rotation)
# create data frame with factor loadings
df <- as.data.frame(pcadata.rotate$loadings[, seq_len(ncol(pcadata.rotate$loadings))])
# ----------------------------
# check if user defined labels have been supplied
# if not, use variable names from data frame
# ----------------------------
if (is.null(var.labels)) var.labels <- row.names(df)
# ----------------------------
# Prepare length of labels
# ----------------------------
if (!is.null(var.labels)) {
# wrap long variable labels
var.labels <- sjmisc::word_wrap(var.labels, wrap.labels, "<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 seq_len(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) < fctr.load.tlrn) {
# 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) {
# return a vector with index numbers indicating which items
# loads the highest on which factor
return(apply(dataframe, 1, function(x) which.max(abs(x))))
}
# --------------------------------------------------------
# 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 seq_len(length(unique(itemloadings)))) {
# calculate cronbach's alpha for those cases that all have the
# highest loading on the same factor
cbv <- c(cbv, performance::cronbachs_alpha(stats::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 {
message("Cronbach's Alpha can only be calculated when having a data frame with each component / variable as column.")
alphaValues <- NULL
show.cronb <- 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 fctr.load.tlrn
# -------------------------------------
removableItems <- getRemovableItems(df)
# -------------------------------------
# retrieve kmo and msa for data set
# -------------------------------------
kmo <- NULL
if (show.msa) kmo <- psych::KMO(data)
# -------------------------------------
# variance
# -------------------------------------
pov <- cpov <- NULL
if (show.var) {
pov <- summary(pcadata)$importance[2, seq_len(pcadata.kaiser)]
cpov <- summary(pcadata)$importance[3, seq_len(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 seq_len(ncol(df))) {
page.content <- paste0(page.content, sprintf(" <th class=\"thead\">Component %i</th>\n", i))
}
# check if msa column should be shown
if (show.msa) 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 seq_len(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 (alternate.rows) arcstring <- ifelse(sjmisc::is_even(i), " 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, var.labels[i]))
# iterate all columns
for (j in seq_len(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 (show.msa) 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 (show.var) {
# 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", string.pov))
# 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 (show.msa) 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", string.cpov))
# 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 (show.msa) page.content <- paste0(page.content, " <td class=\"tdata centeralign cpov\"></td>\n")
page.content <- paste0(page.content, " </tr>\n")
}
# -------------------------------------
# cronbach's alpha
# -------------------------------------
if (show.cronb && !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 seq_len(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 (show.msa) page.content <- paste0(page.content, " <td class=\"tdata centeralign cronbach\"></td>\n")
page.content <- paste0(page.content, " </tr>\n")
}
# -------------------------------------
# Kaiser-Meyer-Olkin-Kriterium
# -------------------------------------
if (show.msa) {
# 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")
}
# -------------------------------------
# show rotation
# -------------------------------------
colsp <- ncol(df) + 1
if (show.msa) colsp <- colsp + 1
page.content <- paste0(page.content, " <tr>\n")
page.content <- paste0(page.content, sprintf(" <td class=\"tdata rightalign rotate\" colspan=\"%i\">%s-rotation</td>\n", colsp, rotation))
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 <- apply(df, 1, function(x) which.max(abs(x)))
# -------------------------------------
# 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, fixed = TRUE, useBytes = TRUE)
knitr <- gsub("<table", sprintf("<table style=\"%s\"", css.table), knitr, fixed = TRUE, useBytes = TRUE)
knitr <- gsub("<caption", sprintf("<caption style=\"%s\"", css.caption), knitr, fixed = TRUE, useBytes = TRUE)
# -------------------------------------
# replace class-attributes with inline-style-definitions
# -------------------------------------
knitr <- gsub(tag.tdata, css.tdata, knitr, fixed = TRUE, useBytes = TRUE)
knitr <- gsub(tag.thead, css.thead, knitr, fixed = TRUE, useBytes = TRUE)
knitr <- gsub(tag.centeralign, css.centeralign, knitr, fixed = TRUE, useBytes = TRUE)
knitr <- gsub(tag.rightalign, css.rightalign, knitr, fixed = TRUE, useBytes = TRUE)
knitr <- gsub(tag.cronbach, css.cronbach, knitr, fixed = TRUE, useBytes = TRUE)
knitr <- gsub(tag.msa, css.msa, knitr, fixed = TRUE, useBytes = TRUE)
knitr <- gsub(tag.pov, css.pov, knitr, fixed = TRUE, useBytes = TRUE)
knitr <- gsub(tag.arc, css.arc, knitr, fixed = TRUE, useBytes = TRUE)
knitr <- gsub(tag.cpov, css.cpov, knitr, fixed = TRUE, useBytes = TRUE)
knitr <- gsub(tag.kmo, css.kmo, knitr, fixed = TRUE, useBytes = TRUE)
knitr <- gsub(tag.rotate, css.rotate, knitr, fixed = TRUE, useBytes = TRUE)
knitr <- gsub(tag.minval, css.minval, knitr, fixed = TRUE, useBytes = TRUE)
knitr <- gsub(tag.removable, css.removable, knitr, fixed = TRUE, useBytes = TRUE)
knitr <- gsub(tag.firsttablerow, css.firsttablerow, knitr, fixed = TRUE, useBytes = TRUE)
knitr <- gsub(tag.firsttablecol, css.firsttablecol, knitr, fixed = TRUE, useBytes = TRUE)
# -------------------------------------
# remove spaces?
# -------------------------------------
if (remove.spaces) {
knitr <- sju.rmspc(knitr)
toWrite <- sju.rmspc(toWrite)
page.content <- sju.rmspc(page.content)
}
# -------------------------------------
# return results
# -------------------------------------
structure(class = c("sjTable", "sjtpca"),
list(page.style = page.style,
page.content = page.content,
page.complete = toWrite,
knitr = knitr,
factor.index = factorindex,
removed.items = removableItems,
file = file,
header = table.header,
viewer = use.viewer))
}
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