ggstatsplot (version 0.1.2)

grouped_ggpiestats: Grouped pie charts with statistical tests

Description

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

Usage

grouped_ggpiestats(data, main, condition = NULL, counts = NULL,
  grouping.var, title.prefix = NULL, ratio = NULL, paired = FALSE,
  results.subtitle = TRUE, factor.levels = NULL, stat.title = NULL,
  sample.size.label = TRUE, label.separator = "\n",
  label.text.size = 4, label.fill.color = "white",
  label.fill.alpha = 1, bf.message = TRUE,
  sampling.plan = "indepMulti", fixed.margin = "rows",
  prior.concentration = 1, subtitle = NULL, caption = NULL,
  conf.level = 0.95, bf.prior = 0.707, nboot = 100,
  simulate.p.value = FALSE, B = 2000, bias.correct = FALSE,
  legend.title = NULL, facet.wrap.name = NULL, k = 2, perc.k = 0,
  slice.label = "percentage", facet.proptest = TRUE,
  ggtheme = ggplot2::theme_bw(), ggstatsplot.layer = TRUE,
  package = "RColorBrewer", palette = "Dark2", direction = 1,
  ggplot.component = NULL, return = "plot", messages = TRUE,
  x = NULL, y = NULL, ...)

Arguments

data

A dataframe (or a tibble) from which variables specified are to be taken. A matrix or tables will not be accepted.

main

The variable to use as the rows in the contingency table.

condition

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.

counts

A string naming a variable in data containing counts, or NULL if each row represents a single observation (Default).

grouping.var

A single grouping variable (can be entered either as a bare name x or as a string "x").

title.prefix

Character string specifying the prefix text for the fixed plot title (name of each factor level) (Default: NULL). If NULL, the variable name entered for grouping.var will be used.

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. This means if there are two levels this will be ratio = c(0.5,0.5) or if there are four levels this will be ratio = c(0.25,0.25,0.25,0.25), etc.

paired

Logical indicating whether data came from a within-subjects or repeated measures design study (Default: FALSE). If TRUE, McNemar's test subtitle will be returned. If FALSE, Pearson's chi-square test will be returned.

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.

factor.levels

A character vector with labels for factor levels of main variable.

stat.title

Title for the effect being investigated with the chi-square test. The default is NULL, i.e. no title will be added to describe the effect being shown. An example of a stat.title argument will be something like "main x condition" or "interaction".

sample.size.label

Logical that decides whether sample size information should be displayed for each level of the grouping variable y (Default: TRUE).

label.separator

If "both" counts and proportion information is to be displayed in a label, this argument decides whether these two pieces of information are going to be on the same line (" ") or on separate lines ("\n").

label.text.size

Numeric that decides text size for slice/bar labels (Default: 4).

label.fill.color

Character that specifies fill color for slice/bar labels (Default: white).

label.fill.alpha

Numeric that specifies fill color transparency or "alpha" for slice/bar labels (Default: 1 range 0 to 1).

bf.message

Logical that decides whether to display a caption with results from Bayes Factor test in favor of the null hypothesis (default: FALSE).

sampling.plan

Character describing the sampling plan. Possible options are "indepMulti" (independent multinomial; default), "poisson", "jointMulti" (joint multinomial), "hypergeom" (hypergeometric). For more, see ?BayesFactor::contingencyTableBF().

fixed.margin

For the independent multinomial sampling plan, which margin is fixed ("rows" or "cols"). Defaults to "rows".

prior.concentration

Specifies the prior concentration parameter, set to 1 by default. It indexes the expected deviation from the null hypothesis under the alternative, and corresponds to Gunel and Dickey's (1974) "a" parameter.

subtitle

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

caption

The text for the plot caption.

conf.level

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

bf.prior

A numeric value between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes Factors.

nboot

Number of bootstrap samples for computing confidence interval for the effect size (Default: 100).

simulate.p.value

a logical indicating whether to compute p-values by Monte Carlo simulation.

B

an integer specifying the number of replicates used in the Monte Carlo test.

bias.correct

If TRUE, a bias correction will be applied to Cramer's V.

legend.title

Title text for the legend.

facet.wrap.name

The text for the facet_wrap variable label.

k

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

perc.k

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

slice.label

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

facet.proptest

Decides whether proportion test for main variable is to be carried out for each level of condition (Default: TRUE).

ggtheme

A function, ggplot2 theme name. Default value is ggplot2::theme_bw(). Any of the ggplot2 themes, or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.).

ggstatsplot.layer

Logical that decides whether theme_ggstatsplot theme elements are to be displayed along with the selected ggtheme (Default: TRUE). theme_ggstatsplot is an opinionated theme layer that override some aspects of the selected ggtheme.

package

Name of package from which the palette is desired as string or symbol.

palette

If a character string (e.g., "Set1"), will use that named palette. If a number, will index into the list of palettes of appropriate type. Default palette is "Dark2".

direction

Either 1 or -1. If -1 the palette will be reversed.

ggplot.component

A ggplot component to be added to the plot prepared by ggstatsplot. This argument is primarily helpful for grouped_ variant of the current function. Default is NULL. The argument should be entered as a function. If the given function has an argument axes.range.restrict and if it has been set to TRUE, the added ggplot component might not work as expected.

return

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.

messages

Decides whether messages references, notes, and warnings are to be displayed (Default: TRUE).

x

The variable to use as the rows in the contingency table.

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.

...

Arguments passed on to combine_plots

title.text

String or plotmath expression to be drawn as title for the combined plot.

title.color

Text color for title.

title.size

Point size of title text.

title.vjust

Vertical justification for title. Default = 0.5 (centered on y). 0 = baseline at y, 1 = ascender at y.

title.hjust

Horizontal justification for title. Default = 0.5 (centered on x). 0 = flush-left at x, 1 = flush-right.

title.fontface

The font face ("plain", "bold" (default), "italic", "bold.italic") for title.

caption.text

String or plotmath expression to be drawn as the caption for the combined plot.

caption.color

Text color for caption.

caption.size

Point size of title text.

caption.vjust

Vertical justification for caption. Default = 0.5 (centered on y). 0 = baseline at y, 1 = ascender at y.

caption.hjust

Horizontal justification for caption. Default = 0.5 (centered on x). 0 = flush-left at x, 1 = flush-right.

caption.fontface

The font face ("plain" (default), "bold", "italic", "bold.italic") for caption.

sub.text

The label with which the combined plot should be annotated. Can be a plotmath expression.

sub.color

Text color for annotation label (Default: "black").

sub.size

Point size of annotation text (Default: 12).

sub.x

The x position of annotation label (Default: 0.5).

sub.y

The y position of annotation label (Default: 0.5).

sub.hjust

Horizontal justification for annotation label (Default: 0.5).

sub.vjust

Vertical justification for annotation label (Default: 0.5).

sub.vpadding

Vertical padding. The total vertical space added to the label, given in grid units. By default, this is added equally above and below the label. However, by changing the y and vjust parameters, this can be changed (Default: grid::unit(1, "lines")).

sub.fontface

The font face ("plain" (default), "bold", "italic", "bold.italic") for the annotation label.

sub.angle

Angle at which annotation label is to be drawn (Default: 0).

sub.lineheight

Line height of annotation label.

title.caption.rel.heights

Numerical vector of relative columns heights while combining (title, plot, caption).

title.rel.heights

Numerical vector of relative columns heights while combining (title, plot).

caption.rel.heights

Numerical vector of relative columns heights while combining (plot, caption).

Value

Unlike a number of statistical softwares, ggstatsplot doesn't provide the option for Yates' correction for the Pearson's chi-squared statistic. This is due to compelling amount of Monte-Carlo simulation research which suggests that the Yates' correction is overly conservative, even in small sample sizes. As such it is recommended that it should not ever be applied in practice (Camilli & Hopkins, 1978, 1979; Feinberg, 1980; Larntz, 1978; Thompson, 1988).

For more about how the effect size measures and their confidence intervals are computed, see ?rcompanion::cohenG, ?rcompanion::cramerV, and ?rcompanion::cramerVFit.

References

https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggpiestats.html

See Also

ggbarstats, ggpiestats, grouped_ggbarstats

Examples

Run this code
# NOT RUN {
# }
# NOT RUN {
# grouped one-sample proportion tests
ggstatsplot::grouped_ggpiestats(
  data = mtcars,
  grouping.var = am,
  x = cyl
)

# without condition and with count data
library(jmv)

ggstatsplot::grouped_ggpiestats(
  data = as.data.frame(HairEyeColor),
  x = Hair,
  counts = Freq,
  grouping.var = Sex
)

# the following will take slightly more amount of time
# for reproducibility
set.seed(123)

# let's create a smaller dataframe
diamonds_short <- ggplot2::diamonds %>%
  dplyr::filter(.data = ., cut %in% c("Fair", "Very Good", "Ideal")) %>%
  dplyr::sample_frac(tbl = ., size = 0.10)

# plot
ggstatsplot::grouped_ggpiestats(
  data = diamonds_short,
  x = color,
  y = clarity,
  grouping.var = cut,
  nboot = 20,
  sampling.plan = "poisson",
  title.prefix = "Quality",
  slice.label = "both",
  messages = FALSE,
  perc.k = 1,
  nrow = 3
)
# }

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