Shows the results of a computed correlation as HTML table. Requires either a data.frame or a matrix with correlation coefficients as returned by the cor-function.

tab_corr(
data,
na.deletion = c("listwise", "pairwise"),
corr.method = c("pearson", "spearman", "kendall"),
title = NULL,
var.labels = NULL,
wrap.labels = 40,
show.p = TRUE,
p.numeric = FALSE,
val.rm = NULL,
digits = 3,
triangle = "both",
string.diag = NULL,
CSS = NULL,
encoding = NULL,
file = NULL,
use.viewer = TRUE,
remove.spaces = TRUE
)

## Arguments

data Matrix with correlation coefficients as returned by the cor-function, or a data.frame of variables where correlations between columns should be computed. Indicates how missing values are treated. May be either "listwise" (default) or "pairwise". May be abbreviated. Indicates the correlation computation method. May be one of "pearson" (default), "spearman" or "kendall". May be abbreviated. String, will be used as table caption. Character vector with variable names, which will be used to label variables in the output. Numeric, determines how many chars of the value, variable or axis labels are displayed in one line and when a line break is inserted. Logical, if TRUE, p-values are also printed. Logical, if TRUE, the p-values are printed as numbers. If FALSE (default), asterisks are used. Logical, if TRUE (default), non-significant correlation-values appear faded (by using a lighter grey text color). See 'Note'. Specify a number between 0 and 1 to suppress the output of correlation values that are smaller than val.rm. The absolute correlation values are used, so a correlation value of -.5 would be greater than val.rm = .4 and thus not be omitted. By default, this argument is NULL, hence all values are shown in the table. If a correlation value is below the specified value of val.rm, it is still printed to the HTML table, but made "invisible" with white foreground color. You can use the CSS argument ("css.valueremove") to change color and appearance of those correlation value that are smaller than the limit specified by val.rm. Amount of decimals for estimates Indicates whether only the upper right (use "upper"), lower left (use "lower") or both (use "both") triangles of the correlation table is filled with values. Default is "both". You can specifiy the inital letter only. A vector with string values of the same length as ncol(data) (number of correlated items) that can be used to display content in the diagonal cells where row and column item are identical (i.e. the "self-correlation"). By defauilt, this argument is NULL and the diagnal cells are empty. A list with user-defined style-sheet-definitions, according to the official CSS syntax. See 'Details' or this package-vignette. Character vector, indicating the charset encoding used for variable and value labels. Default is "UTF-8". For Windows Systems, encoding = "Windows-1252" might be necessary for proper display of special characters. Destination file, if the output should be saved as file. If NULL (default), the output will be saved as temporary file and opened either in the IDE's viewer pane or the default web browser. Logical, if TRUE, the HTML table is shown in the IDE's viewer pane. If FALSE or no viewer available, the HTML table is opened in a web browser. Logical, if TRUE, leading spaces are removed from all lines in the final string that contains the html-data. Use this, if you want to remove parantheses for html-tags. The html-source may look less pretty, but it may help when exporting html-tables to office tools.

## Value

Invisibly returns

• the web page style sheet (page.style),

• the web page content (page.content),

• the complete html-output (page.complete) and

• the html-table with inline-css for use with knitr (knitr)

for further use.

## Note

If data is a matrix with correlation coefficients as returned by the cor-function, p-values can't be computed. Thus, show.p, p.numeric and fade.ns only have an effect if data is a data.frame.

## Examples

if (FALSE) {
if (interactive()) {
# Data from the EUROFAMCARE sample dataset
library(sjmisc)
data(efc)

# retrieve variable and value labels
varlabs <- get_label(efc)

# recveive first item of COPE-index scale
start <- which(colnames(efc) == "c83cop2")
# recveive last item of COPE-index scale
end <- which(colnames(efc) == "c88cop7")

# create data frame with COPE-index scale
mydf <- data.frame(efc[, c(start:end)])
colnames(mydf) <- varlabs[c(start:end)]

# we have high correlations here, because all items
# belong to one factor.
tab_corr(mydf, p.numeric = TRUE)

# auto-detection of labels, only lower triangle
tab_corr(efc[, c(start:end)], triangle = "lower")

# auto-detection of labels, only lower triangle, all correlation
# values smaller than 0.3 are not shown in the table
tab_corr(efc[, c(start:end)], triangle = "lower", val.rm = 0.3)

# auto-detection of labels, only lower triangle, all correlation
# values smaller than 0.3 are printed in blue
tab_corr(efc[, c(start:end)], triangle = "lower",val.rm = 0.3,
CSS = list(css.valueremove = 'color:blue;'))
}}