ggdotplotstats: Dot plot/chart for labeled numeric data

In ggstatsplot: 'ggplot2' Based Plots with Statistical Details

Dot plot/chart for labeled numeric data

Description

A dot chart (as described by William S. Cleveland) with statistical details from one-sample test.

The point estimate (and associated uncertainty) displayed depends on the type of statistics selected:

• mean for parametric statistics

• median for non-parametric statistics

• trimmed mean for robust statistics

• MAP estimator for Bayesian statistics

Usage

ggdotplotstats(
  data,
  x,
  y,
  xlab = NULL,
  ylab = NULL,
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  type = "parametric",
  test.value = 0,
  alternative = "two.sided",
  bf.prior = 0.707,
  bf.message = TRUE,
  conf.int = TRUE,
  conf.level = 0.95,
  tr = 0.2,
  digits = 2L,
  results.subtitle = TRUE,
  point.args = list(color = "black", size = 3, shape = 16),
  errorbar.args = list(width = 0, na.rm = TRUE),
  centrality.plotting = TRUE,
  centrality.type = type,
  centrality.line.args = list(color = "blue", linewidth = 1, linetype = "dashed"),
  ggplot.component = NULL,
  ggtheme = ggstatsplot::theme_ggstatsplot(),
  ...
)

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.
x	A numeric variable from the data frame data.
y	Label or grouping variable. Each level of y is shown as a single dot: if a level has several rows, x is summarized using the centrality measure for the chosen type (see above), and the one-sample test is then carried out on these per-level summaries (i.e., the sample size is the number of levels of y).
xlab	Label for x axis variable. If NULL (default), variable name for x will be used.
ylab	Label for y axis variable. If NULL (default), variable name for y will be used.
title	The text for the plot title.
subtitle	The text for the plot subtitle. Will work only if results.subtitle = FALSE.
caption	The text for the plot caption. It will be replaced by the Bayes Factor caption whenever that is displayed (see bf.message).
type	A character specifying the type of statistical approach: "parametric" "nonparametric" "robust" "bayes" You can specify just the initial letter (e.g. "np" or "bf"). Matching is on the initial lowercase letter only, so any other value (including capitalized values such as "Bayes") falls back to "parametric" without a warning.
test.value	A number indicating the true value of the mean (Default: 0).
alternative	a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". You can specify just the initial letter.
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.
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).
conf.int	Logical. Decides whether to display confidence intervals as error bars (Default: TRUE).
conf.level	Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95).
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.
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()).
results.subtitle	Decides whether the results of statistical tests are to be displayed as a subtitle (Default: TRUE). Setting this to FALSE also skips the automatic Bayes Factor caption. See the individual annotation arguments to control other plot details.
point.args	A list of additional aesthetic arguments to be passed to the ggplot2::geom_point().
errorbar.args	Additional arguments that will be passed to ggplot2::geom_errorbar() geom. Please see documentation for that function to know more about these arguments.
centrality.plotting	Logical that decides whether central 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 a different 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: "parametric" (for mean) "nonparametric" (for median) "robust" (for trimmed mean) "bayes" (for MAP estimator) Just as type argument, abbreviations are also accepted.
centrality.line.args	A list of additional aesthetic arguments to be passed to the ggplot2::geom_vline() used to display the lines corresponding to the centrality parameter.
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 contain. 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.
...	Currently ignored.

Details

Rows with a missing value in either x or y are removed before plotting and analysis.

For details, see: https://www.indrapatil.com/ggstatsplot/articles/web_only/ggdotplotstats.html

Value

A ggplot object, which can be further modified with {ggplot2} functions. Use extract_stats() to get the statistical details shown in the plot as data frames.

Summary of graphics

graphical element	geom used	argument for further modification
point estimates	ggplot2::geom_point()	point.args
error bars	ggplot2::geom_errorbar()	errorbar.args
centrality measure line	ggplot2::geom_vline()	centrality.line.args

One-sample tests

The table below provides summary about:

• statistical test carried out for inferential statistics

• type of effect size estimate and a measure of uncertainty for this estimate

• functions used internally to compute these details

Hypothesis testing

Type	Test	Function used
Parametric	One-sample Student's t-test	stats::t.test()
Non-parametric	One-sample Wilcoxon test	stats::wilcox.test()
Robust	Bootstrap-t method for one-sample test	WRS2::trimcibt()
Bayesian	One-sample Student's t-test	BayesFactor::ttestBF()

Effect size estimation

Type	Effect size	CI available?	Function used
Parametric	Cohen's d, Hedges' g	Yes	effectsize::cohens_d(), effectsize::hedges_g()
Non-parametric	r (rank-biserial correlation)	Yes	effectsize::rank_biserial()
Robust	trimmed mean	Yes	WRS2::trimcibt()
Bayesian	difference	Yes	bayestestR::describe_posterior()

See Also

grouped_gghistostats, gghistostats, grouped_ggdotplotstats

Examples

# for reproducibility
set.seed(123)

# creating a plot
p <- ggdotplotstats(
  data = ggplot2::mpg,
  x = cty,
  y = manufacturer,
  title = "Fuel economy data",
  xlab = "city miles per gallon"
)

# looking at the plot
p

# extracting details from statistical tests
extract_stats(p)

ggstatsplot documentation built on Oct. 18, 2026, 1:07 a.m.