ggdotplotstats {ggstatsplot} | R Documentation |
A dot chart (as described by William S. Cleveland) with statistical details from one-sample test.
ggdotplotstats( data, x, y, xlab = NULL, ylab = NULL, title = NULL, subtitle = NULL, caption = NULL, type = "parametric", test.value = 0, bf.prior = 0.707, bf.message = TRUE, effsize.type = "g", conf.level = 0.95, tr = 0.2, k = 2L, results.subtitle = TRUE, point.args = list(color = "black", size = 3, shape = 16), centrality.plotting = TRUE, centrality.type = type, centrality.line.args = list(color = "blue", linewidth = 1, linetype = "dashed"), ggplot.component = NULL, ggtheme = ggstatsplot::theme_ggstatsplot(), ... )
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 |
A numeric variable from the data frame |
y |
Label or grouping variable. |
xlab |
Label for |
ylab |
Labels for |
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 |
type |
A character specifying the type of statistical approach:
You can specify just the initial letter. |
test.value |
A number indicating the true value of the mean (Default:
|
bf.prior |
A number between |
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: |
effsize.type |
Type of effect size needed for parametric tests. The
argument can be |
conf.level |
Scalar between |
tr |
Trim level for the mean when carrying out |
k |
Number of digits after decimal point (should be an integer)
(Default: |
results.subtitle |
Decides whether the results of statistical tests are
to be displayed as a subtitle (Default: |
point.args |
A list of additional aesthetic arguments passed to
|
centrality.plotting |
Logical that decides whether centrality tendency
measure is to be displayed as a point with a label (Default:
If you want default centrality parameter, you can specify this using
|
centrality.type |
Decides which centrality parameter is to be displayed.
The default is to choose the same as
Just as |
centrality.line.args |
A list of additional aesthetic arguments to be
passed to the |
ggplot.component |
A |
ggtheme |
A |
... |
Currently ignored. |
For details, see: https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggdotplotstats.html
graphical element | geom used | argument for further modification |
histogram bin | ggplot2::stat_bin() | bin.args |
centrality measure line | ggplot2::geom_vline() | centrality.line.args |
normality curve | ggplot2::stat_function() | normal.curve.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 | Test | Function used |
Parametric | One-sample Student's t-test | stats::t.test() |
Non-parametric | One-sample Wilcoxon test | stats::wilcox.test() |
Robust | Bootstrap-t method for one-sample test | WRS2::trimcibt() |
Bayesian | One-sample Student's t-test | BayesFactor::ttestBF() |
Effect size estimation
Type | Effect size | CI available? | Function used |
Parametric | Cohen's d, Hedge's g | Yes | effectsize::cohens_d() , effectsize::hedges_g() |
Non-parametric | r (rank-biserial correlation) | Yes | effectsize::rank_biserial() |
Robust | trimmed mean | Yes | WRS2::trimcibt() |
Bayes Factor | difference | Yes | bayestestR::describe_posterior() |
grouped_gghistostats
, gghistostats
,
grouped_ggdotplotstats
# for reproducibility set.seed(123) # creating a plot p <- ggdotplotstats( data = ggplot2::mpg, x = cty, y = manufacturer, title = "Fuel economy data", xlab = "city miles per gallon" ) # looking at the plot p # extracting details from statistical tests extract_stats(p)