# ggbetweenstats

0th

Percentile

##### Violin plots for group or condition comparisons in between-subjects designs.

A combination of box and violin plots along with jittered data points for between-subjects designs with statistical details included in the plot as a subtitle.

##### Usage
ggbetweenstats(data, x, y, plot.type = "boxviolin",
type = "parametric", effsize.type = "unbiased",
effsize.noncentral = FALSE, xlab = NULL, ylab = NULL,
caption = NULL, title = NULL, sample.size.label = TRUE, k = 3,
var.equal = FALSE, nboot = 100, tr = 0.1, conf.level = 0.95,
conf.type = "norm", 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.coef = 1.5, mean.plotting = TRUE, mean.ci = FALSE,
mean.size = 5, mean.color = "darkred",
ggtheme = ggplot2::theme_bw(), palette = "Dark2",
point.jitter.width = NULL, point.jitter.height = 0.1,
point.dodge.width = 0.6, messages = TRUE)
##### Arguments
data

Dataframe from which variables specified are preferentially to be taken.

x

The grouping variable.

y

The response - a vector of length the number of rows of x.

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 mix of box and violin plots; default).

type

Type of statistic expected ("parametric" or "nonparametric" or "robust").Corresponding abbreviations are also accepted: "p" (for parametric), "np" (nonparametric), "r" (robust), resp.

effsize.type

Type of effect size needed for parametric tests ("biased" (Cohen's d for t-test; partial eta-squared for anova) or "unbiased" (Hedge's g for t-test; partial omega-squared for anova)).

effsize.noncentral

Logical indicating whether to use non-central t-distributions for computing the 95 or Hedge's g (Default: FALSE).

xlab

Label for x axis variable.

ylab

Label for y axis variable.

caption

The text for the plot caption.

title

The text for the plot title.

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 decimal places expected for results.

var.equal

A logical variable indicating whether to treat the two variances as being equal (Default: FALSE).

nboot

Number of bootstrap samples for computing 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.

conf.level

Scalar between 0 and 1. If NULL, the defaults return 95% lower and upper confidence intervals (0.95).

conf.type

A vector of character strings representing the type of confidence intervals required from bootstrapping for partial eta- and omega-squared. The value should be any subset of the values "norm", "basic", "perc", "bca". For more, see ?boot::boot.ci.

mean.label.size, mean.label.fontface, 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.

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.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 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").

ggtheme

A function, ggplot2 theme name. Default value is ggplot2::theme_bw(). Allowed values are the official ggplot2 themes, including ggplot2::theme_grey(), ggplot2::theme_minimal(), ggplot2::theme_classic(), ggplot2::theme_void(), etc.

palette

If a character string (e.g., "Set1"), will use that named palette. If a number, will index into the list of palettes of appropriate type. Default palette is "Dark2".

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.

messages

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

##### References

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

grouped_ggbetweenstats

##### Aliases
• ggbetweenstats
##### Examples
# NOT RUN {
# to get reproducible results from bootstrapping
set.seed(123)

# simple function call with the defaults
ggstatsplot::ggbetweenstats(
data = datasets::iris,
x = Species,
y = Sepal.Length
)

# more detailed function call
ggstatsplot::ggbetweenstats(
data = datasets::ToothGrowth,
x = supp,
y = len,
plot.type = "box",
xlab = "Supplement type",
ylab = "Tooth length"
)
# }

Documentation reproduced from package ggstatsplot, version 0.0.5, License: GPL-3 | file LICENSE

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