ggbarstats {ggstatsplot} | R Documentation |
Bar charts for categorical data with statistical details included in the plot as a subtitle.
ggbarstats( data, x, y, counts = NULL, type = "parametric", paired = FALSE, results.subtitle = TRUE, label = "percentage", label.args = list(alpha = 1, fill = "white"), k = 2L, proportion.test = results.subtitle, perc.k = 0L, bf.message = TRUE, ratio = NULL, conf.level = 0.95, sampling.plan = "indepMulti", fixed.margin = "rows", prior.concentration = 1, title = NULL, subtitle = NULL, caption = NULL, legend.title = NULL, xlab = NULL, ylab = NULL, ggtheme = ggstatsplot::theme_ggstatsplot(), package = "RColorBrewer", palette = "Dark2", ggplot.component = NULL, ... )
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 |
x |
The variable to use as the rows in the contingency table. Please note that if there are empty factor levels in your variable, they will be dropped. |
y |
The variable to use as the columns in the contingency table.
Please note that if there are empty factor levels in your variable, they
will be dropped. Default is |
counts |
The variable in data containing counts, or |
type |
A character specifying the type of statistical approach:
You can specify just the initial letter. |
paired |
Logical indicating whether data came from a within-subjects or
repeated measures design study (Default: |
results.subtitle |
Decides whether the results of statistical tests are
to be displayed as a subtitle (Default: |
label |
Character decides what information needs to be displayed
on the label in each pie slice. Possible options are |
label.args |
Additional aesthetic arguments that will be passed to
|
k |
Number of digits after decimal point (should be an integer)
(Default: |
proportion.test |
Decides whether proportion test for |
perc.k |
Numeric that decides number of decimal places for percentage
labels (Default: |
bf.message |
Logical that decides whether to display Bayes Factor in
favor of the null hypothesis. This argument is relevant only for
parametric test (Default: |
ratio |
A vector of proportions: the expected proportions for the
proportion test (should sum to 1). Default is |
conf.level |
Scalar between |
sampling.plan |
Character describing the sampling plan. Possible options
are |
fixed.margin |
For the independent multinomial sampling plan, which
margin is fixed ( |
prior.concentration |
Specifies the prior concentration parameter, set
to |
title |
The text for the plot title. |
subtitle |
The text for the plot subtitle. Will work only if
|
caption |
The text for the plot caption. This argument is relevant only
if |
legend.title |
Title text for the legend. |
xlab |
Label for |
ylab |
Labels for |
ggtheme |
A |
package, palette |
Name of the package from which the given palette is to
be extracted. The available palettes and packages can be checked by running
|
ggplot.component |
A |
... |
Currently ignored. |
For details, see: https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggpiestats.html
graphical element | geom used | argument for further modification |
bars | ggplot2::geom_bar() | NA |
descriptive labels | ggplot2::geom_label() | label.args |
The table below provides summary about:
statistical test carried out for inferential statistics
type of effect size estimate and a measure of uncertainty for this estimate
functions used internally to compute these details
Hypothesis testing
Type | Design | Test | Function used |
Parametric/Non-parametric | Unpaired | Pearson's chi-squared test | stats::chisq.test() |
Bayesian | Unpaired | Bayesian Pearson's chi-squared test | BayesFactor::contingencyTableBF() |
Parametric/Non-parametric | Paired | McNemar's chi-squared test | stats::mcnemar.test() |
Bayesian | Paired | No | No |
Effect size estimation
Type | Design | Effect size | CI available? | Function used |
Parametric/Non-parametric | Unpaired | Cramer's V | Yes | effectsize::cramers_v() |
Bayesian | Unpaired | Cramer's V | Yes | effectsize::cramers_v() |
Parametric/Non-parametric | Paired | Cohen's g | Yes | effectsize::cohens_g() |
Bayesian | Paired | No | No | No |
Hypothesis testing
Type | Test | Function used |
Parametric/Non-parametric | Goodness of fit chi-squared test | stats::chisq.test() |
Bayesian | Bayesian Goodness of fit chi-squared test | (custom) |
Effect size estimation
Type | Effect size | CI available? | Function used |
Parametric/Non-parametric | Pearson's C | Yes | effectsize::pearsons_c() |
Bayesian | No | No | No |
grouped_ggbarstats
, ggpiestats
,
grouped_ggpiestats
# for reproducibility set.seed(123) # creating a plot p <- ggbarstats(mtcars, x = vs, y = cyl) # looking at the plot p # extracting details from statistical tests extract_stats(p)