# grouped_ggbetweenstats

##### Violin plots for group or condition comparisons in between-subjects designs repeated across all levels of a grouping variable.

A combined plot of comparison plot created for levels of a grouping variable.

##### Usage

```
grouped_ggbetweenstats(
data,
x,
y,
grouping.var,
title.prefix = NULL,
plot.type = "boxviolin",
type = "parametric",
pairwise.comparisons = FALSE,
pairwise.annotation = "p.value",
pairwise.display = "significant",
p.adjust.method = "holm",
effsize.type = "unbiased",
partial = TRUE,
effsize.noncentral = TRUE,
bf.prior = 0.707,
bf.message = TRUE,
results.subtitle = TRUE,
xlab = NULL,
ylab = NULL,
subtitle = NULL,
stat.title = NULL,
caption = NULL,
sample.size.label = TRUE,
k = 2,
var.equal = FALSE,
conf.level = 0.95,
nboot = 100,
tr = 0.1,
sort = "none",
sort.fun = mean,
axes.range.restrict = FALSE,
mean.label.size = 3,
mean.label.fontface = "bold",
mean.label.color = "black",
notch = FALSE,
notchwidth = 0.5,
linetype = "solid",
outlier.tagging = FALSE,
outlier.label = NULL,
outlier.label.color = "black",
outlier.color = "black",
outlier.shape = 19,
outlier.coef = 1.5,
mean.plotting = TRUE,
mean.ci = FALSE,
mean.size = 5,
mean.color = "darkred",
point.jitter.width = NULL,
point.jitter.height = 0,
point.dodge.width = 0.6,
ggtheme = ggplot2::theme_bw(),
ggstatsplot.layer = TRUE,
package = "RColorBrewer",
palette = "Dark2",
direction = 1,
ggplot.component = NULL,
return = "plot",
messages = TRUE,
...
)
```

##### Arguments

- data
A dataframe (or a tibble) from which variables specified are to be taken. A matrix or tables will

**not**be accepted.- x
The grouping variable from the dataframe

`data`

.- y
The response (a.k.a. outcome or dependent) variable from the dataframe

`data`

.- grouping.var
A single grouping variable (can be entered either as a bare name

`x`

or as a string`"x"`

).- title.prefix
Character string specifying the prefix text for the fixed plot title (name of each factor level) (Default:

`NULL`

). If`NULL`

, the variable name entered for`grouping.var`

will be used.- plot.type
Character describing the

*type*of plot. Currently supported plots are`"box"`

(for pure boxplots),`"violin"`

(for pure violin plots), and`"boxviolin"`

(for a combination of box and violin plots; default).- type
Type of statistic expected (

`"parametric"`

or`"nonparametric"`

or`"robust"`

or`"bayes"`

).Corresponding abbreviations are also accepted:`"p"`

(for parametric),`"np"`

(nonparametric),`"r"`

(robust), or`"bf"`

resp.- pairwise.comparisons
Logical that decides whether pairwise comparisons are to be displayed (default:

`FALSE`

). Please note that**only significant comparisons**will be shown by default. To change this behavior, select appropriate option with`pairwise.display`

argument.- pairwise.annotation
Character that decides the annotations to use for pairwise comparisons. Either

`"p.value"`

(default) or`"asterisk"`

.- pairwise.display
Decides which pairwise comparisons to display. Available options are

`"significant"`

(abbreviation accepted:`"s"`

) or`"non-significant"`

(abbreviation accepted:`"ns"`

) or`"everything"`

/`"all"`

. The default is`"significant"`

. 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.- p.adjust.method
Adjustment method for

*p*-values for multiple comparisons. Possible methods are:`"holm"`

(default),`"hochberg"`

,`"hommel"`

,`"bonferroni"`

,`"BH"`

,`"BY"`

,`"fdr"`

,`"none"`

.- effsize.type
Type of effect size needed for

*parametric*tests. The argument can be`"biased"`

(equivalent to`"d"`

for Cohen's*d*for**t-test**;`"partial_eta"`

for partial eta-squared for**anova**) or`"unbiased"`

(equivalent to`"g"`

Hedge's*g*for**t-test**;`"partial_omega"`

for partial omega-squared for**anova**)).- partial
Logical that decides if partial eta-squared or omega-squared are returned (Default:

`TRUE`

). If`FALSE`

, eta-squared or omega-squared will be returned. Valid only for objects of class`lm`

,`aov`

,`anova`

, or`aovlist`

.- effsize.noncentral
Logical indicating whether to use non-central

*t*-distributions for computing the confidence interval for Cohen's*d*or Hedge's*g*(Default:`TRUE`

).- 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.- 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.- subtitle
The text for the plot subtitle. Will work only if

`results.subtitle = FALSE`

.- stat.title
A character describing the test being run, which will be added as a prefix in the subtitle. The default is

`NULL`

. An example of a`stat.title`

argument will be something like`"Student's t-test: "`

.- caption
The text for the plot caption.

- sample.size.label
Logical that decides whether sample size information should be displayed for each level of the grouping variable

`x`

(Default:`TRUE`

).- k
Number of digits after decimal point (should be an integer) (Default:

`k = 2`

).- var.equal
a logical variable indicating whether to treat the variances in the samples as equal. If

`TRUE`

, then a simple F test for the equality of means in a one-way analysis of variance is performed. If`FALSE`

, an approximate method of Welch (1951) is used, which generalizes the commonly known 2-sample Welch test to the case of arbitrarily many samples.- conf.level
Scalar between 0 and 1. If unspecified, the defaults return

`95%`

lower and upper confidence 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. If you get error stating "Standard error cannot be computed because of Winsorized variance of 0 (e.g., due to ties). Try to decrease the trimming level.", try to play around with the value of`tr`

, which is by default set to`0.1`

. Lowering the value might help.- sort
If

`"ascending"`

(default),`x`

-axis variable factor levels will be sorted based on increasing values of`y`

-axis variable. If`"descending"`

, the opposite. If`"none"`

, no sorting will happen.- sort.fun
The function used to sort (default:

`mean`

).- axes.range.restrict
Logical that decides whether to restrict the axes values ranges to

`min`

and`max`

values of the axes variables (Default:`FALSE`

), only relevant for functions where axes variables are of numeric type.- mean.label.size
Aesthetics for the label displaying mean. Defaults:

`3`

,`"bold"`

,`"black"`

, respectively.- mean.label.fontface
Aesthetics for the label displaying mean. Defaults:

`3`

,`"bold"`

,`"black"`

, respectively.- mean.label.color
Aesthetics for the label displaying mean. Defaults:

`3`

,`"bold"`

,`"black"`

, respectively.- notch
A logical. If

`FALSE`

(default), a standard box plot will be displayed. If`TRUE`

, a notched box plot will be used. Notches are used to compare groups; if the notches of two boxes do not overlap, this suggests that the medians are significantly different. In a notched box plot, the notches extend`1.58 * IQR / sqrt(n)`

. This gives a roughly`95%`

confidence interval for comparing medians. IQR: Inter-Quartile Range.- notchwidth
For a notched box plot, width of the notch relative to the body (default

`0.5`

).- linetype
Character strings (

`"blank"`

,`"solid"`

,`"dashed"`

,`"dotted"`

,`"dotdash"`

,`"longdash"`

, and`"twodash"`

) specifying the type of line to draw box plots (Default:`"solid"`

). Alternatively, the numbers`0`

to`6`

can be used (`0`

for "blank",`1`

for "solid", etc.).- 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.label.color
Color for the label to to put on the outliers that have been tagged (Default:

`"black"`

).- outlier.color
Default aesthetics for outliers (Default:

`"black"`

).- 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.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`

).- mean.plotting
Logical that decides whether mean is to be highlighted and its value to be displayed (Default:

`TRUE`

).- mean.ci
Logical that decides whether

`95%`

confidence interval for mean is to be displayed (Default:`FALSE`

).- mean.size
Point size for the data point corresponding to mean (Default:

`5`

).- mean.color
Color for the data point corresponding to mean (Default:

`"darkred"`

).- point.jitter.width
Numeric specifying the degree of jitter in

`x`

direction. Defaults to`40%`

of the resolution of the data.- point.jitter.height
Numeric specifying the degree of jitter in

`y`

direction. Defaults to`0.1`

.- point.dodge.width
Numeric specifying the amount to dodge in the

`x`

direction. Defaults to`0.60`

.- 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`

.- package
Name of package from which the palette is desired as string or symbol.

- palette
Name of palette as string or symbol.

- direction
Either

`1`

or`-1`

. If`-1`

the palette will be reversed.- ggplot.component
A

`ggplot`

component to be added to the plot prepared by`ggstatsplot`

. This argument is primarily helpful for`grouped_`

variant of the current function. Default is`NULL`

. The argument should be entered as a function. If the given function has an argument`axes.range.restrict`

and if it has been set to`TRUE`

, the added`ggplot`

component*might*not work as expected.- return
Character that describes what is to be returned: can be

`"plot"`

(default) or`"subtitle"`

or`"caption"`

. Setting this to`"subtitle"`

will return the expression containing statistical results. If you have set`results.subtitle = FALSE`

, then this will return a`NULL`

. Setting this to`"caption"`

will return the expression containing details about Bayes Factor analysis, but valid only when`type = "parametric"`

and`bf.message = TRUE`

, otherwise this will return a`NULL`

.- messages
Decides whether messages references, notes, and warnings are to be displayed (Default:

`TRUE`

).- ...
Arguments passed on to

`combine_plots`

`title.text`

String or plotmath expression to be drawn as title for the

*combined plot*.`title.color`

Text color for title.

`title.size`

Point size of title text.

`title.vjust`

Vertical justification for title. Default =

`0.5`

(centered on`y`

).`0`

= baseline at`y`

,`1`

= ascender at`y`

.`title.hjust`

Horizontal justification for title. Default =

`0.5`

(centered on`x`

).`0`

= flush-left at x,`1`

= flush-right.`title.fontface`

The font face (

`"plain"`

,`"bold"`

(default),`"italic"`

,`"bold.italic"`

) for title.`caption.text`

String or plotmath expression to be drawn as the caption for the

*combined plot*.`caption.color`

Text color for caption.

`caption.size`

Point size of title text.

`caption.vjust`

Vertical justification for caption. Default =

`0.5`

(centered on y).`0`

= baseline at y,`1`

= ascender at y.`caption.hjust`

Horizontal justification for caption. Default =

`0.5`

(centered on x).`0`

= flush-left at x,`1`

= flush-right.`caption.fontface`

The font face (

`"plain"`

(default),`"bold"`

,`"italic"`

,`"bold.italic"`

) for caption.`sub.text`

The label with which the

*combined plot*should be annotated. Can be a plotmath expression.`sub.color`

Text color for annotation label (Default:

`"black"`

).`sub.size`

Point size of annotation text (Default:

`12`

).`sub.x`

The x position of annotation label (Default:

`0.5`

).`sub.y`

The y position of annotation label (Default:

`0.5`

).`sub.hjust`

Horizontal justification for annotation label (Default:

`0.5`

).`sub.vjust`

Vertical justification for annotation label (Default:

`0.5`

).`sub.vpadding`

Vertical padding. The total vertical space added to the label, given in grid units. By default, this is added equally above and below the label. However, by changing the y and vjust parameters, this can be changed (Default:

`ggplot2::unit(1, "lines")`

).`sub.fontface`

The font face (

`"plain"`

(default),`"bold"`

,`"italic"`

,`"bold.italic"`

) for the annotation label.`sub.angle`

Angle at which annotation label is to be drawn (Default:

`0`

).`sub.lineheight`

Line height of annotation label.

`title.caption.rel.heights`

Numerical vector of relative columns heights while combining (title, plot, caption).

`title.rel.heights`

Numerical vector of relative columns heights while combining (title, plot).

`caption.rel.heights`

Numerical vector of relative columns heights while combining (plot, caption).

##### Details

For parametric tests, Welch's ANOVA/*t*-test are used as a default (i.e.,
`var.equal = FALSE`

).
References:

ANOVA: Delacre, Leys, Mora, & Lakens,

*PsyArXiv*, 2018*t*-test: Delacre, Lakens, & Leys,*International Review of Social Psychology*, 2017

If robust tests are selected, following tests are used is .

ANOVA: one-way ANOVA on trimmed means (see

`?WRS2::t1way`

)*t*-test: Yuen's test for trimmed means (see`?WRS2::yuen`

)

For more about how the effect size measures (for nonparametric tests) and
their confidence intervals are computed, see `?rcompanion::wilcoxonR`

.

For repeated measures designs, use `ggwithinstats`

.

##### References

https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggbetweenstats.html

##### See Also

##### Examples

```
# NOT RUN {
# to get reproducible results from bootstrapping
set.seed(123)
# the most basic function call
ggstatsplot::grouped_ggbetweenstats(
data = dplyr::filter(ggplot2::mpg, drv != "4"),
x = year,
y = hwy,
grouping.var = drv,
conf.level = 0.99
)
# modifying individual plots using `ggplot.component` argument
ggstatsplot::grouped_ggbetweenstats(
data = dplyr::filter(
ggstatsplot::movies_long,
genre %in% c("Action", "Comedy"),
mpaa %in% c("R", "PG")
),
x = genre,
y = rating,
grouping.var = mpaa,
results.subtitle = FALSE,
ggplot.component = ggplot2::scale_y_continuous(
breaks = seq(1, 9, 1),
limits = (c(1, 9))
),
messages = FALSE
)
# }
```

*Documentation reproduced from package ggstatsplot, version 0.1.4, License: GPL-3 | file LICENSE*