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.
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)Dataframe from which variables specified are preferentially to be taken.
The grouping variable.
The response - a vector of length the number of rows of x.
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 of statistic expected ("parametric" or "nonparametric"
or "robust").Corresponding abbreviations are also accepted: "p" (for
parametric), "np" (nonparametric), "r" (robust), resp.
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)).
Logical indicating whether to use non-central
t-distributions for computing the 95
or Hedge's g (Default: FALSE).
Label for x axis variable.
Label for y axis variable.
The text for the plot caption.
The text for the plot title.
Logical that decides whether sample size information
should be displayed for each level of the grouping variable x (Default:
TRUE).
Number of decimal places expected for results.
A logical variable indicating whether to treat the two
variances as being equal (Default: FALSE).
Number of bootstrap samples for computing effect size (Default:
100).
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.
Scalar between 0 and 1. If NULL, the defaults return
95% lower and upper confidence intervals (0.95).
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.
Aesthetics for
the label displaying mean. Defaults: 3, "bold","black", respectively.
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.
For a notched box plot, width of the notch relative to the
body (default 0.5).
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.).
Decides whether outliers should be tagged (Default:
FALSE).
Label to put on the outliers that have been tagged.
Color for the label to to put on the outliers that
have been tagged (Default: "black").
Default aesthetics for outliers (Default: "black").
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).
Logical that decides whether mean is to be highlighted
and its value to be displayed (Default: TRUE).
Logical that decides whether 95
is to be displayed (Default: FALSE).
Point size for the data point corresponding to mean
(Default: 5).
Color for the data point corresponding to mean (Default:
"darkred").
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.
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".
Numeric specifying the degree of jitter in x
direction. Defaults to 40% of the resolution of the data.
Numeric specifying the degree of jitter in y
direction. Defaults to 0.1.
Numeric specifying the amount to dodge in the x
direction. Defaults to 0.60.
Decides whether messages references, notes, and warnings are
to be displayed (Default: TRUE).
https://indrajeetpatil.github.io/ggstatsplot/articles/ggbetweenstats.html
# 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"
)
# }
Run the code above in your browser using DataCamp Workspace