ggpiestats

0th

Percentile

Pie charts with statistical tests

Pie charts for categorical data with statistical details included in the plot as a subtitle.

Usage
ggpiestats(
  data,
  main,
  condition = NULL,
  counts = 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,
  title = NULL,
  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.

counts

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

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.

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.

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

Name of palette as string or symbol.

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, main

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

y, 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. This argument can not be NULL for ggbarstats function.

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

grouped_ggpiestats, ggbarstats, grouped_ggbarstats

Aliases
  • ggpiestats
Examples
# NOT RUN {
# for reproducibility
set.seed(123)

# one sample goodness of fit proportion test
ggstatsplot::ggpiestats(
  data = ggplot2::msleep,
  x = vore,
  perc.k = 1,
  bf.message = FALSE,
  k = 3
)

# association test (or contingency table analysis)
ggstatsplot::ggpiestats(
  data = mtcars,
  x = vs,
  y = cyl,
  bf.message = TRUE,
  nboot = 10,
  factor.levels = c("0 = V-shaped", "1 = straight"),
  legend.title = "Engine"
)

# using `counts` argument
library(jmv, warn.conflicts = FALSE)

ggstatsplot::ggpiestats(
  data = as.data.frame(HairEyeColor),
  x = Eye,
  counts = Freq
)
# }
Documentation reproduced from package ggstatsplot, version 0.1.4, License: GPL-3 | file LICENSE

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