
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,
fade.ns = TRUE,
val.rm = NULL,
digits = 3,
triangle = "both",
string.diag = NULL,
CSS = NULL,
encoding = NULL,
file = NULL,
use.viewer = TRUE,
remove.spaces = TRUE
)
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.
String, indicating the charset encoding used for variable and
value labels. Default is NULL
, so encoding will be auto-detected
depending on your platform (e.g., "UTF-8"
for Unix and "Windows-1252"
for
Windows OS). Change encoding if specific chars are not properly displayed (e.g. German umlauts).
Destination file, if the output should be saved as file.
If NULL
(default), the output will be saved as temporary file and
openend 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.
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.
# NOT RUN {
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;'))
}
# }
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