x
The variable to use as the rows in the contingency table. Please
note that if there are empty factor levels in your variable, they will be
dropped.
y
The variable to use as the columns in the contingency table.
Please note that if there are empty factor levels in your variable, they
will be dropped. Default is NULL
. If NULL
, onesample proportion test
(a goodness of fit test) will be run for the x
variable. Otherwise an
appropriate association test will be run. This argument can not be NULL
for ggbarstats
function.
proportion.test
Decides whether proportion test for x
variable is to
be carried out for each level of y
. Defaults to results.subtitle
. In
ggbarstats
, only pvalues from this test will be displayed.
perc.k
Numeric that decides number of decimal places for percentage
labels (Default: 0L
).
label
Character decides what information needs to be displayed
on the label in each pie slice. Possible options are "percentage"
(default), "counts"
, "both"
.
label.args
Additional aesthetic arguments that will be passed to
geom_label
.
legend.title
Title text for the legend.
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
.
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 Yaxis. Some themes (e.g.
ggthemes::theme_fivethirtyeight()
) will remove the secondary Yaxis and
thus the details as well.
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
).
paired
Logical indicating whether data came from a withinsubjects or
repeated measures design study (Default: FALSE
). If TRUE
, McNemar's
test expression will be returned. If FALSE
, Pearson's chisquare test will
be returned.
counts
The variable in data containing counts, or NULL
if each row
represents a single observation.
ratio
A vector of proportions: the expected proportions for the
proportion test (should sum to 1). Default is NULL
, which means the null
is equal theoretical proportions across the levels of the nominal variable.
This means if there are two levels this will be ratio = c(0.5,0.5)
or if
there are four levels this will be ratio = c(0.25,0.25,0.25,0.25)
, etc.
sampling.plan
Character describing the sampling plan. Possible options
are "indepMulti"
(independent multinomial; default), "poisson"
,
"jointMulti"
(joint multinomial), "hypergeom"
(hypergeometric). For
more, see ?BayesFactor::contingencyTableBF()
.
fixed.margin
For the independent multinomial sampling plan, which
margin is fixed ("rows"
or "cols"
). Defaults to "rows"
.
prior.concentration
Specifies the prior concentration parameter, set
to 1
by default. It indexes the expected deviation from the null
hypothesis under the alternative, and corresponds to Gunel and Dickey's
(1974) "a"
parameter.
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.