A combination of box and violin plots along with raw (unjittered) data points for within-subjects designs with statistical details included in the plot as a subtitle.
ggwithinstats(data, x, y, type = "parametric",
pairwise.comparisons = FALSE, pairwise.annotation = "asterisk",
pairwise.display = "significant", p.adjust.method = "holm",
effsize.type = "unbiased", partial = TRUE,
effsize.noncentral = TRUE, bf.prior = 0.707, bf.message = TRUE,
sphericity.correction = TRUE, results.subtitle = TRUE, xlab = NULL,
ylab = NULL, caption = NULL, title = NULL, subtitle = NULL,
sample.size.label = TRUE, k = 2, conf.level = 0.95, nboot = 100,
tr = 0.1, path.point = TRUE, path.mean = TRUE, 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.shape = 19, 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(), 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.
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. Only significant comparisons will be shown by
default. (default: FALSE). To change this behavior, select appropriate
option with pairwise.display argument.
Character that decides the annotations to use for
pairwise comparisons. Either "p.value" or "asterisk" (default).
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).
Logical that decides whether to apply correction
to account for violation of sphericity in a repeated measures design ANOVA
(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 caption.
The text for the plot title.
The text for the plot subtitle. Will work only if
results.subtitle = FALSE.
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).
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.
Logical that decides whether individual data
points and means, respectively, should be connected using geom_path. Both
default to TRUE. Note that path.point argument is relevant only when
there are two groups (i.e., in case of a t-test). In case of large number
of data points, it is advisable to set path.point = FALSE as these lines
can overwhelm the plot.
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).
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.
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(). 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).
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,
which will be a NULL if you set results.subtitle = FALSE. Setting this
to "caption" will return the expression containing details about Bayes
Factor analysis, but valid only when type = "p" and bf.message = TRUE,
otherwise this will return a NULL.
Decides whether messages references, notes, and warnings are
to be displayed (Default: TRUE).
For more about how the effect size measures (for nonparametric tests) and
their confidence intervals are computed, see ?rcompanion::wilcoxonPairedR.
For independent measures designs, use ggbetweenstats.
grouped_ggbetweenstats, ggbetweenstats,
grouped_ggwithinstats, pairwise_p
# NOT RUN {
# setup
set.seed(123)
library(ggstatsplot)
# two groups (*t*-test)
ggstatsplot::ggwithinstats(
data = VR_dilemma,
x = modality,
y = score,
xlab = "Presentation modality",
ylab = "Proportion of utilitarian decisions"
)
# more than two groups (anova)
library(WRS2)
ggstatsplot::ggwithinstats(
data = tibble::as_tibble(WineTasting),
x = Wine,
y = Taste,
type = "np",
conf.level = 0.99,
pairwise.comparisons = TRUE,
outlier.tagging = TRUE,
outlier.label = Taster
)
# }
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