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
, one-sample 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 p-values from this test will be displayed.
digits.perc
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
ggplot2::geom_label()
.
label.repel
Whether labels should be repelled using {ggrepel}
package.
This can be helpful in case the labels are overlapping.
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 Y-axis. Some themes (e.g.
ggthemes::theme_fivethirtyeight()
) will remove the secondary Y-axis 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.
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.
paired
Logical indicating whether data came from a within-subjects or
repeated measures design study (Default: FALSE
).
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.
E.g., ratio = c(0.5, 0.5)
for two levels,
ratio = c(0.25, 0.25, 0.25, 0.25)
for four levels, 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.