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Scatterplot with marginal distributions for all levels of a grouping variable

Source: R/ggscatterstats.R
grouped_ggscatterstats.Rd

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

Usage

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

Arguments

data

A data frame (or a tibble) from which variables specified are to be taken. Other data types (e.g., matrix,table, array, etc.) will not be accepted. Additionally, grouped data frames from {dplyr} should be ungrouped before they are entered as data.

...

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.

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,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.

xsidehistogram.args,ysidehistogram.args

A list of arguments passed to respective geom_s from the {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.

digits

Number of digits for rounding or significant figures. May also be "signif" to return significant figures or "scientific" to return scientific notation. Control the number of digits by adding the value as suffix, e.g. digits = "scientific4" to have scientific notation with 4 decimal places, or digits = "signif5" for 5 significant figures (see also signif()).

conf.level

Scalar between 0 and 1 (default: 95% confidence/credible intervals, 0.95). If NULL, no confidence intervals will be computed.

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.

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.

xlab

Label for x axis variable. If NULL (default), variable name for x will be used.

ylab

Labels for y axis variable. If NULL (default), variable name for y will be used.

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.

subtitle

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

caption

The text for the plot caption. This argument is relevant only if bf.message = FALSE.

point.args

A list of additional aesthetic arguments to be passed to the ggplot2::geom_point().

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.

ggtheme

A {ggplot2} theme. Default value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

grouping.var

A single grouping variable.

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

For details, see: https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggscatterstats.html

See also

ggscatterstats, ggcorrmat, grouped_ggcorrmat

Examples

# to ensure reproducibility
set.seed(123)

library(dplyr, warn.conflicts = FALSE)
library(ggplot2)

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_xsidebin()` using `bins = 30`. Pick better value with `binwidth`.
#> `stat_ysidebin()` using `bins = 30`. Pick better value with `binwidth`.
#> `stat_xsidebin()` using `bins = 30`. Pick better value with `binwidth`.
#> `stat_ysidebin()` 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_xsidebin()` using `bins = 30`. Pick better value with `binwidth`.
#> `stat_ysidebin()` using `bins = 30`. Pick better value with `binwidth`.
#> `stat_xsidebin()` using `bins = 30`. Pick better value with `binwidth`.
#> `stat_ysidebin()` using `bins = 30`. Pick better value with `binwidth`.
#> `stat_xsidebin()` using `bins = 30`. Pick better value with `binwidth`.
#> `stat_ysidebin()` 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_xsidebin()` using `bins = 30`. Pick better value with `binwidth`.
#> `stat_ysidebin()` using `bins = 30`. Pick better value with `binwidth`.
#> `stat_xsidebin()` using `bins = 30`. Pick better value with `binwidth`.
#> `stat_ysidebin()` using `bins = 30`. Pick better value with `binwidth`.