Helper function for ggstatsplot::ggcorrmat()
to apply this function across
multiple levels of a given factor and combining the resulting plots using
ggstatsplot::combine_plots()
.
grouped_ggcorrmat(
data,
...,
grouping.var,
plotgrid.args = list(),
annotation.args = list()
)
A data frame from which variables specified are to be taken.
Arguments passed on to ggcorrmat
cor.vars
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.
cor.vars.names
Optional list of names to be used for cor.vars
. The
names should be entered in the same order.
partial
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.
matrix.type
Character, "upper"
(default), "lower"
, or "full"
,
display full matrix, lower triangular or upper triangular matrix.
sig.level
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.
colors
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.
pch
Decides the point shape to be used for insignificant correlation
coefficients (only valid when insig = "pch"
). Default: pch = "cross"
.
ggcorrplot.args
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
.
type
A character specifying the type of statistical approach:
"parametric"
"nonparametric"
"robust"
"bayes"
You can specify just the initial letter.
digits
Number of digits for rounding or significant figures. May also
be "signif"
to return significant figures or "scientific"
to return scientific notation. Control the number of digits by adding the
value as suffix, e.g. digits = "scientific4"
to have scientific
notation with 4 decimal places, or digits = "signif5"
for 5
significant figures (see also signif()
).
conf.level
Scalar between 0
and 1
(default: 95%
confidence/credible intervals, 0.95
). If NULL
, no confidence intervals
will be computed.
tr
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.
bf.prior
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.
p.adjust.method
Adjustment method for p-values for multiple
comparisons. Possible methods are: "holm"
(default), "hochberg"
,
"hommel"
, "bonferroni"
, "BH"
, "BY"
, "fdr"
, "none"
.
subtitle
The text for the plot subtitle. Will work only if
results.subtitle = FALSE
.
caption
The text for the plot caption. This argument is relevant only
if bf.message = FALSE
.
ggplot.component
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.
package,palette
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)
.
ggtheme
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 single grouping variable.
A list
of additional arguments passed to
patchwork::wrap_plots()
, except for guides
argument which is already
separately specified here.
A list
of additional arguments passed to
patchwork::plot_annotation()
.
For details, see: https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggcorrmat.html
ggcorrmat
, ggscatterstats
,
grouped_ggscatterstats
set.seed(123)
grouped_ggcorrmat(
data = iris,
grouping.var = Species,
type = "robust",
p.adjust.method = "holm",
plotgrid.args = list(ncol = 1L),
annotation.args = list(tag_levels = "i")
)
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