pairwise_p_caption

Type of statistic expected (<code>"parametric"</code> or <code>"nonparametric"</code>
or <code>"robust"</code> or <code>"bayes"</code>).Corresponding abbreviations are also accepted:
<code>"p"</code> (for parametric), <code>"np"</code> (nonparametric), <code>"r"</code> (robust), or
<code>"bf"</code>resp.

type

a logical variable indicating whether to treat the
 variances in the samples as equal. If <code>TRUE</code>, then a simple F
 test for the equality of means in a one-way analysis of variance is
 performed. If <code>FALSE</code>, an approximate method of Welch (1951)
 is used, which generalizes the commonly known 2-sample Welch test to
 the case of arbitrarily many samples.

var.equal

a logical indicating whether you want a paired
 t-test.

paired

Adjustment method for p-values for multiple
comparisons. Possible methods are: <code>"holm"</code> (default), <code>"hochberg"</code>,
<code>"hommel"</code>, <code>"bonferroni"</code>, <code>"BH"</code>, <code>"BY"</code>, <code>"fdr"</code>, <code>"none"</code>.

p.adjust.method

caption

Preparing caption in case pairwise comparisons are displayed.

internal

Extension of 'ggplot2', 'ggstatsplot' creates
graphics with details from statistical tests included in the plots
themselves. It is targeted primarily at behavioral sciences community
to provide a one-line code to generate information-rich plots for
statistical analysis of continuous (violin plots, scatterplots,
histograms, dot plots, dot-and-whisker plots) or categorical (pie and
bar charts) data. Currently, it supports only the most common types of
statistical tests: parametric, nonparametric, robust, and bayesian
versions of t-test/anova, correlation analyses, contingency table
analysis, and regression analyses.

pairwise_p_caption: Preparing caption in case pairwise comparisons are displayed.

Description

Usage

Arguments