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.

## Usage

ggwithinstats(
data,
x,
y,
type = "parametric",
pairwise.comparisons = TRUE,
pairwise.display = "significant",
effsize.type = "unbiased",
bf.prior = 0.707,
bf.message = TRUE,
results.subtitle = TRUE,
xlab = NULL,
ylab = NULL,
caption = NULL,
title = NULL,
subtitle = NULL,
k = 2L,
conf.level = 0.95,
nboot = 100L,
tr = 0.2,
centrality.plotting = TRUE,
centrality.type = type,
centrality.point.args = list(size = 5, color = "darkred"),
centrality.label.args = list(size = 3, nudge_x = 0.4, segment.linetype = 4),
centrality.path = TRUE,
centrality.path.args = list(size = 1, color = "red", alpha = 0.5),
point.args = list(size = 3, alpha = 0.5),
point.path = TRUE,
point.path.args = list(alpha = 0.5, linetype = "dashed"),
outlier.tagging = FALSE,
outlier.label = NULL,
outlier.coef = 1.5,
outlier.label.args = list(size = 3),
boxplot.args = list(width = 0.2, alpha = 0.5),
violin.args = list(width = 0.5, alpha = 0.2),
ggsignif.args = list(textsize = 3, tip_length = 0.01),
ggtheme = ggstatsplot::theme_ggstatsplot(),
package = "RColorBrewer",
palette = "Dark2",
ggplot.component = NULL,
output = "plot",
...
)

## Arguments

data

A dataframe (or a tibble) from which variables specified are to be taken. Other data types (e.g., matrix,table, array, etc.) will not be accepted.

x

The grouping (or independent) variable from the dataframe data. In case of a repeated measures or within-subjects design, if subject.id argument is not available or not explicitly specified, the function assumes that the data has already been sorted by such an id by the user and creates an internal identifier. So if your data is not sorted, the results can be inaccurate when there are more than two levels in x and there are NAs present. The data is expected to be sorted by user in subject-1,subject-2, ..., pattern.

y

The response (or outcome or dependent) variable from the dataframe data.

type

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

You can specify just the initial letter.

pairwise.comparisons

Logical that decides whether pairwise comparisons are to be displayed (default: TRUE). Please note that only significant comparisons will be shown by default. To change this behavior, select appropriate option with pairwise.display argument. The pairwise comparison dataframes are prepared using the pairwise_comparisons function. For more details about pairwise comparisons, see the documentation for that function.

pairwise.display

Decides which pairwise comparisons to display. Available options are:

• "significant" (abbreviation accepted: "s")

• "non-significant" (abbreviation accepted: "ns")

• "all"

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".

effsize.type

Type of effect size needed for parametric tests. The argument can be "eta" (partial eta-squared) or "omega" (partial omega-squared).

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.

caption

The text for the plot caption.

title

The text for the plot title.

subtitle

The text for the plot subtitle. Will work only if results.subtitle = FALSE.

k

Number of digits after decimal point (should be an integer) (Default: k = 2L).

conf.level

Scalar between 0 and 1. If unspecified, the defaults return 95% confidence/credible intervals (0.95).

nboot

Number of bootstrap samples for computing confidence interval for the effect size (Default: 100L).

tr

Trim level for the mean when carrying out robust tests. In case of an error, try reducing the value of tr, which is by default set to 0.2. Lowering the value might help.

centrality.plotting

Logical that decides whether centrality tendency measure is to be displayed as a point with a label (Default: TRUE). Function decides which central tendency measure to show depending on the type argument.

• mean for parametric statistics

• median for non-parametric statistics

• trimmed mean for robust statistics

• MAP estimator for Bayesian statistics

If you want default centrality parameter, you can specify this using centrality.type argument.

centrality.type

Decides which centrality parameter is to be displayed. The default is to choose the same as type argument. You can specify this to be:

• "parameteric" (for mean)

• "nonparametric" (for median)

• robust (for trimmed mean)

• bayes (for MAP estimator)

Just as type argument, abbreviations are also accepted.

centrality.point.args

A list of additional aesthetic arguments to be passed to geom_point and ggrepel::geom_label_repel geoms, which are involved in mean plotting.

centrality.label.args

A list of additional aesthetic arguments to be passed to geom_point and ggrepel::geom_label_repel geoms, which are involved in mean plotting.

centrality.path.args, point.path.args

A list of additional aesthetic arguments passed on to geom_path connecting raw data points and mean points.

point.args

A list of additional aesthetic arguments to be passed to the geom_point displaying the raw data.

point.path, centrality.path

Logical that decides whether individual data points and means, respectively, should be connected using geom_path. Both default to TRUE. Note that point.path 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 point.path = FALSE as these lines can overwhelm the plot.

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.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).

outlier.label.args

A list of additional aesthetic arguments to be passed to ggrepel::geom_label_repel for outlier label plotting.

boxplot.args

A list of additional aesthetic arguments passed on to geom_boxplot.

violin.args

A list of additional aesthetic arguments to be passed to the geom_violin.

ggsignif.args

A list of additional aesthetic arguments to be passed to ggsignif::geom_signif.

ggtheme

A {ggplot2} theme. Default value is ggstatsplot::theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.).

package

Name of the package from which the given palette is to be extracted. The available palettes and packages can be checked by running View(paletteer::palettes_d_names).

palette

Name of the package from which the given palette is to be extracted. The available palettes and packages can be checked by running View(paletteer::palettes_d_names).

ggplot.component

A ggplot component to be added to the plot prepared by {ggstatsplot}. This argument is primarily helpful for grouped_ variants of all primary functions. Default is NULL. The argument should be entered as a {ggplot2} function or a list of {ggplot2} functions.

output

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.

...

Currently ignored.

## Note

To carry out Bayesian analysis for ANOVA designs, you will need to install the development version of BayesFactor (0.9.12-4.3). You can download it by running: remotes::install_github("richarddmorey/BayesFactor/pkg/BayesFactor").

grouped_ggbetweenstats, ggbetweenstats, grouped_ggwithinstats

## Examples

# \donttest{
if (require("PMCMRplus")) {
# setup
set.seed(123)
library(ggstatsplot)
library(dplyr, warn.conflicts = FALSE)

# two groups (*t*-test)
ggwithinstats(
data = filter(bugs_long, condition %in% c("HDHF", "HDLF")),
x    = condition,
y    = desire
)

# more than two groups (anova)
library(WRS2)

ggwithinstats(
data            = WineTasting,
x               = Wine,
y               = Taste,
type            = "r",
outlier.tagging = TRUE,
outlier.label   = Taster
)
}

# }