A combined plot of comparison plot created for levels of a grouping variable.
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, ...)A dataframe (or a tibble) from which variables specified are to be taken. A matrix or tables will not be accepted.
The grouping variable from the dataframe data.
The response (a.k.a. outcome or dependent) variable from the
dataframe data.
A single grouping variable (can be entered either as a
bare name x or as a string "x").
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.
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 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.
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.
Character that decides the annotations to use for
pairwise comparisons. Either "p.value" (default) or "asterisk".
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.
Adjustment method for p-values for multiple
comparisons. Possible methods are: "holm" (default), "hochberg",
"hommel", "bonferroni", "BH", "BY", "fdr", "none".
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)).
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.
Logical indicating whether to use non-central
t-distributions for computing the confidence interval for Cohen's d
or Hedge's g (Default: TRUE).
A number between 0.5 and 2 (default 0.707), the prior
width to use in calculating Bayes factors.
Logical that decides whether to display Bayes Factor in
favor of the null hypothesis. This argument is relevant only for
parametric test (Default: TRUE).
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.
Labels for x and y axis variables. If NULL (default),
variable names for x and y will be used.
Labels for x and y axis variables. If NULL (default),
variable names for x and y will be used.
The text for the plot subtitle. Will work only if
results.subtitle = FALSE.
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: ".
The text for the plot caption.
Logical that decides whether sample size information
should be displayed for each level of the grouping variable x (Default:
TRUE).
Number of digits after decimal point (should be an integer)
(Default: k = 2).
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.
Scalar between 0 and 1. If unspecified, the defaults return
95% lower and upper confidence intervals (0.95).
Number of bootstrap samples for computing confidence interval
for the 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.
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.
The function used to sort (default: mean).
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.
Aesthetics for
the label displaying mean. Defaults: 3, "bold","black", respectively.
Aesthetics for
the label displaying mean. Defaults: 3, "bold","black", respectively.
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. This
can't be the same as x argument.
Color for the label to to put on the outliers that
have been tagged (Default: "black").
Default aesthetics for outliers (Default: "black").
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.
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% confidence interval for
mean 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").
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.
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.).
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.
Name of package from which the palette is desired as string or symbol.
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".
Either 1 or -1. If -1 the palette will be reversed.
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.
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.
Decides whether messages references, notes, and warnings are
to be displayed (Default: TRUE).
Arguments passed on to combine_plots
String or plotmath expression to be drawn as title for the combined plot.
Text color for title.
Point size of title text.
Vertical justification for title. Default = 0.5
(centered on y). 0 = baseline at y, 1 = ascender at y.
Horizontal justification for title. Default = 0.5
(centered on x). 0 = flush-left at x, 1 = flush-right.
The font face ("plain", "bold" (default),
"italic", "bold.italic") for title.
String or plotmath expression to be drawn as the caption for the combined plot.
Text color for caption.
Point size of title text.
Vertical justification for caption. Default = 0.5
(centered on y). 0 = baseline at y, 1 = ascender at y.
Horizontal justification for caption. Default = 0.5
(centered on x). 0 = flush-left at x, 1 = flush-right.
The font face ("plain" (default), "bold",
"italic", "bold.italic") for caption.
The label with which the combined plot should be annotated. Can be a plotmath expression.
Text color for annotation label (Default: "black").
Point size of annotation text (Default: 12).
The x position of annotation label (Default: 0.5).
The y position of annotation label (Default: 0.5).
Horizontal justification for annotation label (Default:
0.5).
Vertical justification for annotation label (Default:
0.5).
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: grid::unit(1, "lines")).
The font face ("plain" (default), "bold", "italic",
"bold.italic") for the annotation label.
Angle at which annotation label is to be drawn (Default:
0).
Line height of annotation label.
Numerical vector of relative columns heights while combining (title, plot, caption).
Numerical vector of relative columns heights while combining (title, plot).
Numerical vector of relative columns heights while combining (plot, caption).
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.
https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggbetweenstats.html
# 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)),
messages = FALSE
)
# }
# NOT RUN {
# }
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