Grouped bar charts with statistical tests

Helper function for ggstatsplot::ggbarstats() to apply this function across multiple levels of a given factor and combining the resulting plots using ggstatsplot::combine_plots().

Usage

grouped_ggbarstats(
  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 ggbarstats

label.args

Additional aesthetic arguments that will be passed to ggplot2::geom_label().

sample.size.label.args

Additional aesthetic arguments that will be passed to ggplot2::geom_text().

xlab

Label for x axis. If NULL (default), the name of the y variable is used (no label if y is NULL), since bars are drawn for each level of y.

ylab

Label for y axis. If NULL (default), no label is shown.

x

The variable to use as the rows in the contingency table. Note that empty factor levels are not dropped: they are shown in the legend and counted (with zero observations) in the statistical test. Use droplevels() beforehand if this is not intended.

y

The variable to use as the columns in the contingency table. Default is NULL. If NULL, one-sample proportion test (a goodness of fit test) will be run for the x variable. Otherwise an appropriate association test will be run.

proportion.test

Decides whether proportion test for x variable is to be carried out for each level of y. Defaults to results.subtitle. In ggbarstats(), only p-values from this test will be displayed. Always FALSE when type = "bayes" or when y is NULL.

bf.message

Logical that decides whether to display Bayes Factor in favor of the null hypothesis as a caption. This argument is relevant only for non-Bayesian types and unpaired designs (paired = FALSE) (Default: TRUE).

digits.perc

Numeric that decides number of decimal places for percentage labels (Default: 0L).

label

Character that decides what information needs to be displayed on the label in each pie slice. Possible options are "percentage" (default), "counts", "both".

legend.title

Title text for the legend. If NULL (default), the name of the x variable is used.

p.adjust.method

Adjustment method for p-values for multiple comparisons. Possible methods are: "holm" (default), "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none".

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. It will be replaced by the Bayes Factor caption whenever that is displayed (see bf.message).

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.

palette

Name of the discrete palette in "package::palette" format to be used for coloring (via {paletteer}). Run View(paletteer::palettes_d_names) to see all available options.

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.

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.

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.

paired

Logical indicating whether data came from a within-subjects or repeated measures design study (Default: FALSE).

counts

The variable in data containing counts, or NULL if each row represents a single observation.

ratio

A vector of proportions: the expected proportions for the proportion test (should sum to 1). Default is NULL, which means the null is equal theoretical proportions across the levels of the nominal variable. E.g., ratio = c(0.5, 0.5) for two levels, ratio = c(0.25, 0.25, 0.25, 0.25) for four levels, etc.

grouping.var

A single grouping variable. A separate plot is created for each of its levels (in factor level order, or in order of appearance for character variables). Rows with a missing value in this variable are removed.

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().

Value

A patchwork object combining one plot per level of grouping.var (see combine_plots()). Applying extract_stats() to it returns a list with the statistical details for each of these plots.

Details

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

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

See also

ggbarstats, ggpiestats, grouped_ggpiestats

Examples

set.seed(123)
# grouped one-sample proportion test
grouped_ggbarstats(
  data = mtcars,
  x = cyl,
  grouping.var = am,
  annotation.args = list(title = "Cylinder distribution by transmission type")
)