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.
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. If set to "none"
, no pairwise comparisons
will be 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
.
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 ggplot2::geom_point()
displaying the raw data.
boxplot.args
A list of additional aesthetic arguments passed on to
ggplot2::geom_boxplot()
.
violin.args
A list of additional aesthetic arguments to be passed to
the ggplot2::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 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 {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.
x
The grouping (or independent) variable from data
. In case of a
repeated measures or within-subjects 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
subject-1,subject-2, ..., 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.
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.
effsize.type
Type of effect size needed for parametric tests. The
argument can be "eta"
(partial eta-squared) or "omega"
(partial
omega-squared).
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
).