Grouped scatterplots from {ggplot2} combined with marginal distribution plots with statistical details added as a subtitle.

## Usage

grouped_ggscatterstats(
data,
...,
grouping.var,
output = "plot",
plotgrid.args = list(),
annotation.args = list()
)

## 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.

...

Arguments passed on to ggscatterstats

label.var

Variable to use for points labels entered as a symbol (e.g. var1).

label.expression

An expression evaluating to a logical vector that determines the subset of data points to label (e.g. y < 4 & z < 20). While using this argument with purrr::pmap, you will have to provide a quoted expression (e.g. quote(y < 4 & z < 20)).

point.label.args

A list of additional aesthetic arguments to be passed to ggrepel::geom_label_repel geom used to display the labels.

smooth.line.args

A list of additional aesthetic arguments to be passed to geom_smooth geom used to display the regression line.

point.args

A list of additional aesthetic arguments to be passed to geom_point geom used to display the raw data points.

marginal

Decides whether marginal distributions will be plotted on axes using ggside functions. The default is TRUE. The package ggside must already be installed by the user.

point.width.jitter

Degree of jitter in x and y direction, respectively. Defaults to 0 (0%) of the resolution of the data. Note that the jitter should not be specified in the point.args because this information will be passed to two different geoms: one displaying the points and the other displaying the *labels for these points.

point.height.jitter

Degree of jitter in x and y direction, respectively. Defaults to 0 (0%) of the resolution of the data. Note that the jitter should not be specified in the point.args because this information will be passed to two different geoms: one displaying the points and the other displaying the *labels for these points.

xfill

Character describing color fill for x and y axes marginal distributions (default: "#009E73" (for x) and "#D55E00" (for y)). Note that the defaults are colorblind-friendly.

yfill

Character describing color fill for x and y axes marginal distributions (default: "#009E73" (for x) and "#D55E00" (for y)). Note that the defaults are colorblind-friendly.

xsidehistogram.args

A list of arguments passed to respective geom_s from ggside package to change the marginal distribution histograms plots.

ysidehistogram.args

A list of arguments passed to respective geom_s from ggside package to change the marginal distribution histograms plots.

x

The column in data containing the explanatory variable to be plotted on the x-axis.

y

The column in data containing the response (outcome) variable to be plotted on the y-axis.

type

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

You can specify just the initial letter.

conf.level

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

bf.prior

A number between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes factors and posterior estimates. In addition to numeric arguments, several named values are also recognized: "medium", "wide", and "ultrawide", corresponding to r scale values of 1/2, sqrt(2)/2, and 1, respectively. In case of an ANOVA, this value corresponds to scale for fixed effects.

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.

k

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

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.

subtitle

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

caption

The text for the plot caption.

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.).

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.

grouping.var

A single grouping variable.

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.

plotgrid.args

A list of additional arguments passed to patchwork::wrap_plots, except for guides argument which is already separately specified here.

annotation.args

A list of additional arguments passed to patchwork::plot_annotation.

## Details

ggscatterstats, ggcorrmat, grouped_ggcorrmat

## Examples

# to ensure reproducibility
set.seed(123)
library(ggstatsplot)
library(dplyr, warn.conflicts = FALSE)
library(ggplot2)

# basic function call
grouped_ggscatterstats(
data             = filter(movies_long, genre == "Comedy" | genre == "Drama"),
x                = length,
y                = rating,
type             = "robust",
grouping.var     = genre,
ggplot.component = list(geom_rug(sides = "b"))
)
#> stat_bin() using bins = 30. Pick better value with binwidth.
#> stat_bin() using bins = 30. Pick better value with binwidth.
#> stat_bin() using bins = 30. Pick better value with binwidth.
#> stat_bin() using bins = 30. Pick better value with binwidth.

# using labeling
# (also show how to modify basic plot from within function call)
grouped_ggscatterstats(
data             = filter(ggplot2::mpg, cyl != 5),
x                = displ,
y                = hwy,
grouping.var     = cyl,
type             = "robust",
label.var        = manufacturer,
label.expression = hwy > 25 & displ > 2.5,
ggplot.component = scale_y_continuous(sec.axis = dup_axis())
)
#> stat_bin() using bins = 30. Pick better value with binwidth.
#> stat_bin() using bins = 30. Pick better value with binwidth.
#> stat_bin() using bins = 30. Pick better value with binwidth.
#> stat_bin() using bins = 30. Pick better value with binwidth.
#> stat_bin() using bins = 30. Pick better value with binwidth.
#> stat_bin() using bins = 30. Pick better value with binwidth.

# labeling without expression
grouped_ggscatterstats(
data            = filter(movies_long, rating == 7, genre %in% c("Drama", "Comedy")),
x               = budget,
y               = length,
grouping.var    = genre,
bf.message      = FALSE,
label.var       = "title",
annotation.args = list(tag_levels = "a")
)
#> stat_bin() using bins = 30. Pick better value with binwidth.
#> stat_bin() using bins = 30. Pick better value with binwidth.
#> stat_bin() using bins = 30. Pick better value with binwidth.
#> stat_bin() using bins = 30. Pick better value with binwidth.