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
Labels for x
and y
axis variables. If NULL
(default),
variable names for x
and y
will be used.
ylab
Labels for x
and y
axis variables. If NULL
(default),
variable names for x
and 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
pairwiseComparisons::pairwise_comparisons
function. For more details
about pairwise comparisons, see the documentation for that function.
p.adjust.method
Adjustment method for p-values 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 uber-cluttered
when you have multiple groups being compared and scores of pairwise
comparisons being displayed.
bf.prior
A number between 0.5
and 2
(default 0.707
), the prior
width to use in calculating Bayes factors.
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.
outlier.color
Default aesthetics for outliers (Default: "black"
).
outlier.tagging
Decides whether outliers should be tagged (Default:
FALSE
).
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 Inter-Quartile 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 non-parametric 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
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)
.
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
A list of additional aesthetic
arguments to be passed to ggplot2::geom_point
and
ggrepel::geom_label_repel
geoms, which are involved in mean plotting.
centrality.label.args
A list of additional aesthetic
arguments to be passed to ggplot2::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 function, ggplot2
theme name. Default value is
ggplot2::theme_bw()
. Any of the ggplot2
themes, or themes from
extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight()
,
hrbrthemes::theme_ipsum_ps()
, etc.).
ggstatsplot.layer
Logical that decides whether theme_ggstatsplot
theme elements are to be displayed along with the selected ggtheme
(Default: TRUE
). theme_ggstatsplot
is an opinionated theme layer that
override some aspects of the selected ggtheme
.
type
A character specifying the type of statistical approach.
Four possible options:
"parametric"
"nonparametric"
"robust"
"bayes"
Corresponding abbreviations are also accepted: "p"
(for parametric),
"np"
(for nonparametric), "r"
(for robust), or "bf"
(for Bayesian).
effsize.type
Type of effect size needed for parametric tests. The
argument can be "eta"
(partial eta-squared) or "omega"
(partial
omega-squared).
k
Number of digits after decimal point (should be an integer)
(Default: k = 2L
).
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.
conf.level
Scalar between 0
and 1
. If unspecified, the defaults
return 95%
confidence/credible intervals (0.95
).
nboot
Number of bootstrap samples for computing confidence interval
for the effect size (Default: 100
).
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.