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.varsList 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.namesOptional list of names to be used for cor.vars. The
names should be entered in the same order.
partialCan 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.typeCharacter, "upper" (default), "lower", or "full",
display full matrix, lower triangular or upper triangular matrix.
sig.levelSignificance 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.
colorsA 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.
pchDecides the point shape to be used for insignificant correlation
coefficients (only valid when insig = "pch"). Default: pch = "cross".
ggcorrplot.argsA 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.
typeA character specifying the type of statistical approach:
"parametric"
"nonparametric"
"robust"
"bayes"
You can specify just the initial letter.
digitsNumber 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.levelScalar between 0 and 1 (default: 95%
confidence/credible intervals, 0.95). If NULL, no confidence intervals
will be computed.
trTrim 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.priorA 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.methodAdjustment method for p-values for multiple
comparisons. Possible methods are: "holm" (default), "hochberg",
"hommel", "bonferroni", "BH", "BY", "fdr", "none".
subtitleThe text for the plot subtitle. Will work only if
results.subtitle = FALSE.
captionThe text for the plot caption. This argument is relevant only
if bf.message = FALSE.
ggplot.componentA 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,paletteName 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).
ggthemeA {ggplot2} theme. Default value is
theme_ggstatsplot(). Any of the {ggplot2} themes (e.g.,
ggplot2::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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