Correlation matrix or a data frame containing results from pairwise
correlation tests. The package internally uses ggcorrplot::ggcorrplot for
creating the visualization matrix, while the correlation analysis is carried
out using the correlation::correlation function.
ggcorrmat(
data,
cor.vars = NULL,
cor.vars.names = NULL,
output = "plot",
matrix.type = "upper",
type = "parametric",
tr = 0.2,
partial = FALSE,
k = 2L,
sig.level = 0.05,
conf.level = 0.95,
bf.prior = 0.707,
p.adjust.method = "holm",
pch = "cross",
ggcorrplot.args = list(method = "square", outline.color = "black", pch.cex = 14),
package = "RColorBrewer",
palette = "Dark2",
colors = c("#E69F00", "white", "#009E73"),
ggtheme = ggstatsplot::theme_ggstatsplot(),
ggplot.component = NULL,
title = NULL,
subtitle = NULL,
caption = NULL,
...
)Dataframe from which variables specified are preferentially to be taken.
List of variables for which the correlation matrix is to be
computed and visualized. If NULL (default), all numeric variables from
data will be used.
Optional list of names to be used for cor.vars. The
names should be entered in the same order.
Character that decides expected output from this function. If
"plot", the visualization matrix will be returned. If "dataframe" (or
literally anything other than "plot"), a data frame containing all details
from statistical analyses (e.g., correlation coefficients, statistic
values, p-values, no. of observations, etc.) will be returned.
Character, "upper" (default), "lower", or "full",
display full matrix, lower triangular or upper triangular matrix.
A character specifying the type of statistical approach:
"parametric"
"nonparametric"
"robust"
"bayes"
You can specify just the initial letter.
Trim level for the mean when carrying out robust tests. In case
of an error, try reducing the value of tr, which is by default set to
0.2. Lowering the value might help.
Can be TRUE for partial correlations. For Bayesian partial
correlations, "full" instead of pseudo-Bayesian partial correlations (i.e.,
Bayesian correlation based on frequentist partialization) are returned.
Number of digits after decimal point (should be an integer)
(Default: k = 2L).
Significance level (Default: 0.05). If the p-value in
p-value matrix is bigger than sig.level, then the corresponding
correlation coefficient is regarded as insignificant and flagged as such in
the plot. Relevant only when output = "plot".
Scalar between 0 and 1. If unspecified, the defaults
return 95% confidence/credible intervals (0.95).
A number between 0.5 and 2 (default 0.707), the prior
width to use in calculating Bayes factors and posterior estimates. In
addition to numeric arguments, several named values are also recognized:
"medium", "wide", and "ultrawide", corresponding to r scale values
of 1/2, sqrt(2)/2, and 1, respectively. In case of an ANOVA, this value
corresponds to scale for fixed effects.
Adjustment method for p-values for multiple
comparisons. Possible methods are: "holm" (default), "hochberg",
"hommel", "bonferroni", "BH", "BY", "fdr", "none".
Decides the point shape to be used for insignificant correlation
coefficients (only valid when insig = "pch"). Default: pch = "cross".
A list of additional (mostly aesthetic) arguments that
will be passed to ggcorrplot::ggcorrplot function. The list should avoid
any of the following arguments since they are already internally being
used: corr, method, p.mat, sig.level, ggtheme, colors, lab,
pch, legend.title, digits.
Name of the package from which the given palette is to
be extracted. The available palettes and packages can be checked by running
View(paletteer::palettes_d_names).
A vector of 3 colors for low, mid, and high correlation values.
If set to NULL, manual specification of colors will be turned off and 3
colors from the specified palette from package will be selected.
A {ggplot2} theme. Default value is
ggstatsplot::theme_ggstatsplot(). Any of the {ggplot2} themes (e.g.,
theme_bw()), or themes from extension packages are allowed (e.g.,
ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.).
But note that sometimes these themes will remove some of the details that
{ggstatsplot} plots typically contains. For example, if relevant,
ggbetweenstats() shows details about multiple comparison test as a label
on the secondary Y-axis. Some themes (e.g.
ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and
thus the details as well.
A ggplot component to be added to the plot prepared
by {ggstatsplot}. This argument is primarily helpful for grouped_
variants of all primary functions. Default is NULL. The argument should
be entered as a {ggplot2} function or a list of {ggplot2} functions.
The text for the plot title.
The text for the plot subtitle. Will work only if
results.subtitle = FALSE.
The text for the plot caption. This argument is relevant only
if bf.message = FALSE.
Currently ignored.
For details, see: https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggcorrmat.html
grouped_ggcorrmat ggscatterstats
grouped_ggscatterstats
# for reproducibility
set.seed(123)
library(ggstatsplot)
# to get a plot (assumes that `ggcorrplot` is installed)
if (require("ggcorrplot")) ggcorrmat(iris)
# to get a data frame
ggcorrmat(
data = ggplot2::msleep,
cor.vars = sleep_total:bodywt,
partial = TRUE,
output = "dataframe"
)
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