Grouped pie charts with statistical tests

Applies ggpiestats() across all levels of grouping.var and combines the resulting plots using combine_plots().

Usage

grouped_ggpiestats(
  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 ggpiestats

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. If NULL (default), a one-sample proportion test (a goodness of fit test) is run for the x variable. Otherwise, an appropriate association test is run.

proportion.test

Logical that decides whether a proportion test for x is carried out for each level of y. Defaults to results.subtitle. ggbarstats() displays only the p-values from this test. Always FALSE when type = "bayes", when y is NULL, or when x has only one level.

bf.message

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

digits.perc

Number of decimal places for percentage labels (Default: 0L).

label

Character that decides what each label displays: "percentage" (default), "counts", or "both".

label.args

A list of additional aesthetic arguments passed to ggplot2::geom_label() (or ggrepel::geom_label_repel() if label.repel = TRUE).

label.repel

Logical that decides whether labels are repelled using {ggrepel} to avoid overlaps (Default: FALSE).

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

Logical that decides whether the results of statistical tests are displayed as a subtitle (Default: TRUE). Setting this to FALSE also skips the automatic Bayes Factor caption. Other plot details have their own arguments.

subtitle

The text for the plot subtitle. Used 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 {ggplot2} component, or a list of components, to add to the plot (Default: NULL). This is mostly helpful for the grouped_ variants, where it is applied to each individual plot.

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: theme_ggstatsplot()). Any {ggplot2} theme (e.g., ggplot2::theme_bw()) or theme from an extension package (e.g., ggthemes::theme_fivethirtyeight()) can be used. Note that some themes remove plot details. For example, ggthemes::theme_fivethirtyeight() removes the secondary Y-axis, which ggbetweenstats() uses to show details about pairwise comparisons.

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.

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).

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). Only relevant for two-way tables (i.e., when y is supplied), and paired designs are only supported for frequentist tests (McNemar's test). For a two-way table with type = "bayes", paired is ignored and the Bayesian test of independence for unpaired data is run instead. For one-way tables (y = NULL), paired has no effect.

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, which has its own argument.

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/ggpiestats.html

See also

ggpiestats(), ggbarstats(), grouped_ggbarstats()

Examples

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