# ggpiestats

##### 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

##### 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*