plot.type
Character describing the type of plot. Currently supported
plots are "box"
(for only boxplots), "violin"
(for only violin plots),
and "boxviolin"
(for a combination of box and violin plots; default).
xlab
Label for x
axis variable. If NULL
(default),
variable name for x
will be used.
ylab
Labels for y
axis variable. If NULL
(default),
variable name for y
will be used.
pairwise.comparisons
Logical that decides whether pairwise comparisons
are to be displayed (default: TRUE
). Please note that only
significant comparisons will be shown by default. To change this
behavior, select appropriate option with pairwise.display
argument. The
pairwise comparison dataframes are prepared using the
pairwise_comparisons
function. For more details
about pairwise comparisons, see the documentation for that function.
p.adjust.method
Adjustment method for pvalues for multiple
comparisons. Possible methods are: "holm"
(default), "hochberg"
,
"hommel"
, "bonferroni"
, "BH"
, "BY"
, "fdr"
, "none"
.
pairwise.display
Decides which pairwise comparisons to display.
Available options are:
You can use this argument to make sure that your plot is not ubercluttered
when you have multiple groups being compared and scores of pairwise
comparisons being displayed.
bf.message
Logical that decides whether to display Bayes Factor in
favor of the null hypothesis. This argument is relevant only for
parametric test (Default: TRUE
).
results.subtitle
Decides whether the results of statistical tests are
to be displayed as a subtitle (Default: TRUE
). If set to FALSE
, only
the plot will be returned.
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
.
outlier.color
Default aesthetics for outliers (Default: "black"
).
outlier.tagging
Decides whether outliers should be tagged (Default:
FALSE
).
outlier.label
Label to put on the outliers that have been tagged. This
can't be the same as x
argument.
outlier.shape
Hiding the outliers can be achieved by setting
outlier.shape = NA
. Importantly, this does not remove the outliers,
it only hides them, so the range calculated for the y
axis will be
the same with outliers shown and outliers hidden.
outlier.label.args
A list of additional aesthetic arguments to be
passed to ggrepel::geom_label_repel
for outlier label plotting.
outlier.coef
Coefficient for outlier detection using Tukey's method.
With Tukey's method, outliers are below (1st Quartile) or above (3rd
Quartile) outlier.coef
times the InterQuartile Range (IQR) (Default:
1.5
).
centrality.plotting
Logical that decides whether centrality tendency
measure is to be displayed as a point with a label (Default: TRUE
).
Function decides which central tendency measure to show depending on the
type
argument.

mean for parametric statistics

median for nonparametric statistics

trimmed mean for robust statistics

MAP estimator for Bayesian statistics
If you want default centrality parameter, you can specify this using
centrality.type
argument.
centrality.type
Decides which centrality parameter is to be displayed.
The default is to choose the same as type
argument. You can specify this
to be:

"parameteric"
(for mean)

"nonparametric"
(for median)

robust
(for trimmed mean)

bayes
(for MAP estimator)
Just as type
argument, abbreviations are also accepted.
point.args
A list of additional aesthetic arguments to be passed to
the geom_point
displaying the raw data.
violin.args
A list of additional aesthetic arguments to be passed to
the geom_violin
.
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)
.
centrality.point.args,centrality.label.args
A list of additional aesthetic
arguments to be passed to geom_point
and
ggrepel::geom_label_repel
geoms, which are involved in mean plotting.
ggsignif.args
A list of additional aesthetic
arguments to be passed to ggsignif::geom_signif
.
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 Yaxis. Some themes (e.g.
ggthemes::theme_fivethirtyeight()
) will remove the secondary Yaxis and
thus the details as well.
x
The grouping (or independent) variable from data
. In case of a
repeated measures or withinsubjects design, if subject.id
argument is
not available or not explicitly specified, the function assumes that the
data has already been sorted by such an id by the user and creates an
internal identifier. So if your data is not sorted, the results can
be inaccurate when there are more than two levels in x
and there are
NA
s present. The data is expected to be sorted by user in
subject1,subject2, ..., pattern.
y
The response (or outcome or dependent) variable from data
.
type
A character specifying the type of statistical approach:

"parametric"

"nonparametric"

"robust"

"bayes"
You can specify just the initial letter.
k
Number of digits after decimal point (should be an integer)
(Default: k = 2L
).
conf.level
Scalar between 0
and 1
. If unspecified, the defaults
return 95%
confidence/credible intervals (0.95
).
effsize.type
Type of effect size needed for parametric tests. The
argument can be "eta"
(partial etasquared) or "omega"
(partial
omegasquared).
var.equal
a logical variable indicating whether to treat the
two variances as being equal. If TRUE
then the pooled
variance is used to estimate the variance otherwise the Welch
(or Satterthwaite) approximation to the degrees of freedom is used.
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.
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.
nboot
Number of bootstrap samples for computing confidence interval
for the effect size (Default: 100L
).