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<!DOCTYPE html>
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<title>'ggplot2' Based Plots with Statistical Details • ggstatsplot</title>
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<meta property="og:title" content="'ggplot2' Based Plots with Statistical Details">
<meta property="og:description" content="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.">
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Articles
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<a href="articles/web_only/ggstatsplot_paper.html">ggstatsplot: ggplot2 Based Plots with Statistical Details</a>
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<a href="articles/web_only/ggwithinstats.html">ggwithinstats</a>
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<a href="articles/web_only/purrr_examples.html">using `ggstatsplot` with the `purrr` package</a>
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<p><!-- README.md is generated from README.Rmd. Please edit that file --></p>
<div id="ggstatsplot-ggplot2-based-plots-with-statistical-details" class="section level1">
<div class="page-header"><h1 class="hasAnchor">
<a href="#ggstatsplot-ggplot2-based-plots-with-statistical-details" class="anchor"></a>ggstatsplot: <code>ggplot2</code> Based Plots with Statistical Details</h1></div>
<table class="table table">
<colgroup>
<col width="20%">
<col width="20%">
<col width="20%">
<col width="20%">
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</colgroup>
<thead><tr class="header">
<th>Package</th>
<th>Status</th>
<th>Usage</th>
<th>GitHub</th>
<th>References</th>
</tr></thead>
<tbody>
<tr class="odd">
<td><a href="https://CRAN.R-project.org/package=ggstatsplot"><img src="http://www.r-pkg.org/badges/version-ago/ggstatsplot" alt="CRAN_Release_Badge"></a></td>
<td><a href="https://travis-ci.org/IndrajeetPatil/ggstatsplot"><img src="https://travis-ci.org/IndrajeetPatil/ggstatsplot.svg?branch=master" alt="Travis Build Status"></a></td>
<td><a href="https://CRAN.R-project.org/package=ggstatsplot"><img src="https://cranlogs.r-pkg.org/badges/last-day/ggstatsplot?color=blue" alt="Daily downloads badge"></a></td>
<td><a href="https://github.com/IndrajeetPatil/ggstatsplot/"><img src="https://img.shields.io/badge/GitHub-0.0.10.9000-orange.svg?style=flat-square" alt="GitHub version"></a></td>
<td><a href="https://indrajeetpatil.github.io/ggstatsplot/"><img src="https://img.shields.io/badge/website-ggstatsplot-orange.svg?colorB=E91E63" alt="Website"></a></td>
</tr>
<tr class="even">
<td><a href="https://cran.r-project.org/web/checks/check_results_ggstatsplot.html"><img src="https://cranchecks.info/badges/summary/ggstatsplot" alt="CRAN Checks"></a></td>
<td><a href="https://ci.appveyor.com/project/IndrajeetPatil/ggstatsplot"><img src="https://ci.appveyor.com/api/projects/status/github/IndrajeetPatil/ggstatsplot?branch=master&svg=true" alt="AppVeyor Build Status"></a></td>
<td><a href="https://CRAN.R-project.org/package=ggstatsplot"><img src="https://cranlogs.r-pkg.org/badges/last-week/ggstatsplot?color=blue" alt="Weekly downloads badge"></a></td>
<td><a href="https://github.com/IndrajeetPatil/ggstatsplot/pulls"><img src="http://githubbadges.herokuapp.com/IndrajeetPatil/ggstatsplot/pulls.svg?style=flat" alt="Github Pending PRs"></a></td>
<td><a href="https://www.rdocumentation.org/packages/ggstatsplot"><img src="https://www.rdocumentation.org/badges/version/ggstatsplot" alt="Rdoc"></a></td>
</tr>
<tr class="odd">
<td><a href="https://cran.r-project.org/"><img src="https://img.shields.io/badge/R%3E%3D-3.5.0-6666ff.svg" alt="minimal R version"></a></td>
<td><a href="https://www.tidyverse.org/lifecycle/"><img src="https://img.shields.io/badge/lifecycle-maturing-blue.svg" alt="lifecycle"></a></td>
<td><a href="https://CRAN.R-project.org/package=ggstatsplot"><img src="https://cranlogs.r-pkg.org/badges/last-month/ggstatsplot?color=blue" alt="Monthly downloads badge"></a></td>
<td><a href="https://github.com/IndrajeetPatil/ggstatsplot/issues"><img src="http://githubbadges.herokuapp.com/IndrajeetPatil/ggstatsplot/issues.svg" alt="Github Issues"></a></td>
<td><a href="https://cran.r-project.org/web/packages/ggstatsplot/vignettes/"><img src="https://img.shields.io/badge/vignettes-0.0.10-orange.svg?colorB=FF5722" alt="vignettes"></a></td>
</tr>
<tr class="even">
<td><a href="https://github.com/IndrajeetPatil/ggstatsplot"><img src="https://img.shields.io/github/languages/code-size/IndrajeetPatil/ggstatsplot.svg" alt="GitHub code size in bytes"></a></td>
<td><a href="https://coveralls.io/github/IndrajeetPatil/ggstatsplot?branch=master"><img src="https://coveralls.io/repos/github/IndrajeetPatil/ggstatsplot/badge.svg?branch=master" alt="Coverage Status"></a></td>
<td><a href="https://CRAN.R-project.org/package=ggstatsplot"><img src="https://cranlogs.r-pkg.org/badges/grand-total/ggstatsplot?color=blue" alt="Total downloads badge"></a></td>
<td><a href="https://github.com/IndrajeetPatil/ggstatsplot"><img src="https://img.shields.io/github/stars/IndrajeetPatil/ggstatsplot.svg?style=social&label=Github" alt="Github Stars"></a></td>
<td><a href="https://doi.org/10.5281/zenodo.2074621"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.2074621.svg" alt="DOI"></a></td>
</tr>
<tr class="odd">
<td><a href="https://www.gnu.org/licenses/gpl-3.0.en.html"><img src="https://img.shields.io/badge/licence-GPL--3-blue.svg" alt="Licence"></a></td>
<td><a href="https://codecov.io/gh/IndrajeetPatil/ggstatsplot?branch=master"><img src="https://codecov.io/gh/IndrajeetPatil/ggstatsplot/branch/master/graph/badge.svg" alt="Codecov test coverage"></a></td>
<td><a href="http://hits.dwyl.io/IndrajeetPatil/ggstatsplot"><img src="http://hits.dwyl.io/IndrajeetPatil/ggstatsplot.svg" alt="HitCount"></a></td>
<td><a href="/commits/master"><img src="https://img.shields.io/badge/last%20change-2019--04--15-yellowgreen.svg" alt="Last-changedate"></a></td>
<td><a href="https://github.com/IndrajeetPatil/ggstatsplot/commits/master"><img src="https://img.shields.io/github/last-commit/IndrajeetPatil/ggstatsplot.svg" alt="GitHub last commit"></a></td>
</tr>
<tr class="even">
<td><a href="https://CRAN.R-project.org/package=ggstatsplot"><img src="https://tinyverse.netlify.com/badge/ggstatsplot" alt="status"></a></td>
<td><a href="https://github.com/IndrajeetPatil/ggstatsplot/blob/master/tests/README.md"><img src="https://img.shields.io/badge/covrpage-Last_Build_2019_01_31-yellowgreen.svg" alt="Covrpage Summary"></a></td>
<td><a href="https://saythanks.io/to/IndrajeetPatil"><img src="https://img.shields.io/badge/Say%20Thanks-!-1EAEDB.svg" alt="saythanks"></a></td>
<td><a href="http://www.repostatus.org/#active"><img src="http://www.repostatus.org/badges/latest/active.svg" alt="Project Status"></a></td>
<td><a href="https://github.com/IndrajeetPatil/ggstatsplot/issues"><img src="https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat" alt="contributions welcome"></a></td>
</tr>
<tr class="odd">
<td><a href="https://gitter.im/ggstatsplot/community"><img src="https://badges.gitter.im/gitterHQ/gitter.png" alt="Gitter chat"></a></td>
<td><a href="https://dependencyci.com/github/IndrajeetPatil/ggstatsplot"><img src="https://dependencyci.com/github/IndrajeetPatil/ggstatsplot/badge" alt="Dependency Status"></a></td>
<td></td>
<td><a href="https://github.com/IndrajeetPatil/ggstatsplot/"><img src="https://img.shields.io/badge/forks-49-blue.svg" alt="Generic badge"></a></td>
<td></td>
</tr>
</tbody>
</table>
</div>
<div id="overview" class="section level1">
<h1 class="hasAnchor">
<a href="#overview" class="anchor"></a>Overview</h1>
<p><a href="https://indrajeetpatil.github.io/ggstatsplot/"><code>ggstatsplot</code></a> is an extension of <a href="https://github.com/tidyverse/ggplot2"><code>ggplot2</code></a> package for creating graphics with details from statistical tests included in the plots themselves and targeted primarily at behavioral sciences community to provide a one-line code to produce information-rich plots. In a typical exploratory data analysis workflow, data visualization and statistical modeling are two different phases: visualization informs modeling, and modeling in its turn can suggest a different visualization method, and so on and so forth. The central idea of <em>ggstatsplot</em> is simple: combine these two phases into one in the form of graphics with statistical details, which makes data exploration simpler and faster.</p>
<p>Currently, it supports only the most common types of statistical tests: <strong>parametric</strong>, <strong>nonparametric</strong>, <strong>robust</strong>, and <strong>bayesian</strong> versions of <strong>t-test</strong>/<strong>anova</strong>, <strong>correlation</strong> analyses, <strong>contingency table</strong> analysis, and <strong>regression</strong> analyses.</p>
<p>It, therefore, produces a limited kinds of plots for the supported analyses:</p>
<ul>
<li>
<strong>violin plots</strong> (for comparisons <em>between</em> groups or conditions),</li>
<li>
<strong>pie charts</strong> and <strong>bar charts</strong> (for categorical data),</li>
<li>
<strong>scatterplots</strong> (for correlations between two variables),</li>
<li>
<strong>correlation matrices</strong> (for correlations between multiple variables),</li>
<li>
<strong>histograms</strong> and <strong>dot plots/charts</strong> (for hypothesis about distributions),</li>
<li>
<strong>dot-and-whisker plots</strong> (for regression models).</li>
</ul>
<p>In addition to these basic plots, <code>ggstatsplot</code> also provides <strong><code>grouped_</code></strong> versions for most functions that makes it easy to repeat the same analysis for any grouping variable.</p>
<p>Future versions will include other types of statistical analyses and plots as well.</p>
</div>
<div id="statistical-reporting" class="section level1">
<h1 class="hasAnchor">
<a href="#statistical-reporting" class="anchor"></a>Statistical reporting</h1>
<p>For all statistical tests reported in the plots, the default template abides by the <a href="https://my.ilstu.edu/~jhkahn/apastats.html">APA</a> gold standard for statistical reporting. For example, here are results from Yuen’s test for trimmed means (robust <em>t</em>-test):</p>
<p><img src="reference/figures/stats_reporting_format.png" align="center"></p>
</div>
<div id="summary-of-supported-statistical-analyses" class="section level1">
<h1 class="hasAnchor">
<a href="#summary-of-supported-statistical-analyses" class="anchor"></a>Summary of supported statistical analyses</h1>
<p>The table below summarizes all the different types of analyses currently supported in this package-</p>
<table class="table table">
<colgroup>
<col width="16%">
<col width="41%">
<col width="9%">
<col width="11%">
<col width="9%">
<col width="11%">
</colgroup>
<thead><tr class="header">
<th>Functions</th>
<th>Description</th>
<th>Parametric</th>
<th>Non-parametric</th>
<th>Robust</th>
<th>Bayes Factor</th>
</tr></thead>
<tbody>
<tr class="odd">
<td><code>ggbetweenstats</code></td>
<td>Between group/condition comparisons</td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
</tr>
<tr class="even">
<td><code>ggwithinstats</code></td>
<td>Within group/condition comparisons</td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
</tr>
<tr class="odd">
<td>
<code>gghistostats</code>, <code>ggdotplotstats</code>
</td>
<td>Distribution of a numeric variable</td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
</tr>
<tr class="even">
<td><code>ggcorrmat</code></td>
<td>Correlation matrix</td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="red">No</font></td>
</tr>
<tr class="odd">
<td><code>ggscatterstats</code></td>
<td>Correlation between two variables</td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
</tr>
<tr class="even">
<td>
<code>ggpiestats</code>, <code>ggbarstats</code>
</td>
<td>Association between categorical variables</td>
<td><font color="green">Yes</font></td>
<td><font color="red">No</font></td>
<td><font color="red">No</font></td>
<td><font color="green">Yes</font></td>
</tr>
<tr class="odd">
<td><code>ggpiestats</code></td>
<td>Proportion test</td>
<td><font color="red">No</font></td>
<td><font color="red">No</font></td>
<td><font color="red">No</font></td>
<td><font color="red">No</font></td>
</tr>
<tr class="even">
<td><code>ggcoefstats</code></td>
<td>Regression model coefficients</td>
<td><font color="green">Yes</font></td>
<td><font color="red">No</font></td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
</tr>
</tbody>
</table>
</div>
<div id="effect-sizes-and-confidence-intervals-available" class="section level1">
<h1 class="hasAnchor">
<a href="#effect-sizes-and-confidence-intervals-available" class="anchor"></a>Effect sizes and confidence intervals available</h1>
<p><code>ggstatsplot</code> provides a wide range of effect sizes and their confidence intervals.</p>
<table class="table table">
<thead><tr class="header">
<th>Test</th>
<th>Parametric</th>
<th>Non-parametric</th>
<th>Robust</th>
<th>Bayes</th>
</tr></thead>
<tbody>
<tr class="odd">
<td>one-sample <em>t</em>-test</td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="red">No</font></td>
</tr>
<tr class="even">
<td>two-sample <em>t</em>-test (between)</td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="red">No</font></td>
</tr>
<tr class="odd">
<td>two-sample <em>t</em>-test (within)</td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="red">No</font></td>
</tr>
<tr class="even">
<td>One-way ANOVA (between)</td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="red">No</font></td>
</tr>
<tr class="odd">
<td>One-way ANOVA (within)</td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="red">No</font></td>
<td><font color="red">No</font></td>
</tr>
<tr class="even">
<td>correlations</td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="red">No</font></td>
</tr>
<tr class="odd">
<td>contingency table</td>
<td><font color="green">Yes</font></td>
<td><code>NA</code></td>
<td><code>NA</code></td>
<td><font color="red">No</font></td>
</tr>
<tr class="even">
<td>goodness of fit</td>
<td><font color="green">Yes</font></td>
<td><code>NA</code></td>
<td><code>NA</code></td>
<td><font color="red">No</font></td>
</tr>
<tr class="odd">
<td>regression</td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="green">Yes</font></td>
<td><font color="red">No</font></td>
</tr>
</tbody>
</table>
</div>
<div id="installation" class="section level1">
<h1 class="hasAnchor">
<a href="#installation" class="anchor"></a>Installation</h1>
<p>To get the latest, stable CRAN release (<code>0.0.10</code>):</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" title="1">utils<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/install.packages">install.packages</a></span>(<span class="dt">pkgs =</span> <span class="st">"ggstatsplot"</span>)</a></code></pre></div>
<p><em>Note</em>: If you are on a linux machine, you will need to have OpenGL libraries installed (specifically, <code>libx11</code>, <code>mesa</code> and Mesa OpenGL Utility library - <code>glu</code>) for the dependency package <code>rgl</code> to work.</p>
<p>You can get the <strong>development</strong> version of the package from GitHub (<code>0.0.10.9000</code>). To see what new changes (and bug fixes) have been made to the package since the last release on <code>CRAN</code>, you can check the detailed log of changes here: <a href="https://indrajeetpatil.github.io/ggstatsplot/news/index.html" class="uri">https://indrajeetpatil.github.io/ggstatsplot/news/index.html</a></p>
<p>If you are in hurry and want to reduce the time of installation, prefer-</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" title="1"><span class="co"># needed package to download from GitHub repo</span></a>
<a class="sourceLine" id="cb2-2" title="2">utils<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/install.packages">install.packages</a></span>(<span class="dt">pkgs =</span> <span class="st">"remotes"</span>)</a>
<a class="sourceLine" id="cb2-3" title="3"></a>
<a class="sourceLine" id="cb2-4" title="4"><span class="co"># downloading the package from GitHub</span></a>
<a class="sourceLine" id="cb2-5" title="5">remotes<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/remotes/topics/install_github">install_github</a></span>(</a>
<a class="sourceLine" id="cb2-6" title="6"> <span class="dt">repo =</span> <span class="st">"IndrajeetPatil/ggstatsplot"</span>, <span class="co"># package path on GitHub</span></a>
<a class="sourceLine" id="cb2-7" title="7"> <span class="dt">dependencies =</span> <span class="ot">FALSE</span>, <span class="co"># assumes you have already installed needed packages</span></a>
<a class="sourceLine" id="cb2-8" title="8"> <span class="dt">quick =</span> <span class="ot">TRUE</span> <span class="co"># skips docs, demos, and vignettes</span></a>
<a class="sourceLine" id="cb2-9" title="9">)</a></code></pre></div>
<p>If time is not a constraint-</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" title="1">remotes<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/remotes/topics/install_github">install_github</a></span>(</a>
<a class="sourceLine" id="cb3-2" title="2"> <span class="dt">repo =</span> <span class="st">"IndrajeetPatil/ggstatsplot"</span>, <span class="co"># package path on GitHub</span></a>
<a class="sourceLine" id="cb3-3" title="3"> <span class="dt">dependencies =</span> <span class="ot">TRUE</span>, <span class="co"># installs packages which ggstatsplot depends on</span></a>
<a class="sourceLine" id="cb3-4" title="4"> <span class="dt">upgrade_dependencies =</span> <span class="ot">TRUE</span> <span class="co"># updates any out of date dependencies</span></a>
<a class="sourceLine" id="cb3-5" title="5">)</a></code></pre></div>
<p>If you are not using the <a href="https://www.rstudio.com/">RStudio IDE</a> and you get an error related to “pandoc” you will either need to remove the argument <code>build_vignettes = TRUE</code> (to avoid building the vignettes) or install <a href="http://pandoc.org/">pandoc</a>. If you have the <code>rmarkdown</code> R package installed then you can check if you have pandoc by running the following in R:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" title="1">rmarkdown<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/rmarkdown/topics/pandoc_available">pandoc_available</a></span>()</a>
<a class="sourceLine" id="cb4-2" title="2"><span class="co">#> [1] TRUE</span></a></code></pre></div>
</div>
<div id="citation" class="section level1">
<h1 class="hasAnchor">
<a href="#citation" class="anchor"></a>Citation</h1>
<p>If you want to cite this package in a scientific journal or in any other context, run the following code in your <code>R</code> console:</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" title="1">utils<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/citation">citation</a></span>(<span class="dt">package =</span> <span class="st">"ggstatsplot"</span>)</a></code></pre></div>
<p>There is currently a publication in preparation corresponding to this package and the citation will be updated once it’s published.</p>
</div>
<div id="documentation-and-examples" class="section level1">
<h1 class="hasAnchor">
<a href="#documentation-and-examples" class="anchor"></a>Documentation and Examples</h1>
<p>To see the detailed documentation for each function in the stable <strong>CRAN</strong> version of the package, see:</p>
<ul>
<li>README: <a href="https://cran.r-project.org/web/packages/ggstatsplot/readme/README.html" class="uri">https://cran.r-project.org/web/packages/ggstatsplot/readme/README.html</a>
</li>
<li>Vignettes: <a href="https://cran.r-project.org/web/packages/ggstatsplot/vignettes/" class="uri">https://cran.r-project.org/web/packages/ggstatsplot/vignettes/</a>
</li>
</ul>
<p>To see the documentation relevant for the <strong>development</strong> version of the package, see the dedicated website for <code>ggstatplot</code>, which is updated after every new commit: <a href="https://indrajeetpatil.github.io/ggstatsplot/" class="uri">https://indrajeetpatil.github.io/ggstatsplot/</a>.</p>
<div id="help" class="section level2">
<h2 class="hasAnchor">
<a href="#help" class="anchor"></a>Help</h2>
<p>In <code>R</code>, documentation for any function can be accessed with the standard <code>help</code> command (e.g., <code><a href="reference/ggbetweenstats.html">?ggbetweenstats</a></code>).</p>
<p>Another handy tool to see arguments to any of the functions is <code>args</code>. For example-</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" title="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/args">args</a></span>(<span class="dt">name =</span> ggstatsplot<span class="op">::</span>specify_decimal_p)</a>
<a class="sourceLine" id="cb6-2" title="2"><span class="co">#> Registered S3 method overwritten by 'broom.mixed':</span></a>
<a class="sourceLine" id="cb6-3" title="3"><span class="co">#> method from </span></a>
<a class="sourceLine" id="cb6-4" title="4"><span class="co">#> tidy.gamlss broom</span></a>
<a class="sourceLine" id="cb6-5" title="5"><span class="co">#> Registered S3 methods overwritten by 'lme4':</span></a>
<a class="sourceLine" id="cb6-6" title="6"><span class="co">#> method from</span></a>
<a class="sourceLine" id="cb6-7" title="7"><span class="co">#> cooks.distance.influence.merMod car </span></a>
<a class="sourceLine" id="cb6-8" title="8"><span class="co">#> influence.merMod car </span></a>
<a class="sourceLine" id="cb6-9" title="9"><span class="co">#> dfbeta.influence.merMod car </span></a>
<a class="sourceLine" id="cb6-10" title="10"><span class="co">#> dfbetas.influence.merMod car</span></a>
<a class="sourceLine" id="cb6-11" title="11"><span class="co">#> Registered S3 method overwritten by 'skimr':</span></a>
<a class="sourceLine" id="cb6-12" title="12"><span class="co">#> method from </span></a>
<a class="sourceLine" id="cb6-13" title="13"><span class="co">#> print.spark pillar</span></a>
<a class="sourceLine" id="cb6-14" title="14"><span class="co">#> function (x, k = 3, p.value = FALSE) </span></a>
<a class="sourceLine" id="cb6-15" title="15"><span class="co">#> NULL</span></a></code></pre></div>
<p>In case you want to look at the function body for any of the functions, just type the name of the function without the parentheses:</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" title="1"><span class="co"># function to convert class of any object to `ggplot` class</span></a>
<a class="sourceLine" id="cb7-2" title="2">ggstatsplot<span class="op">::</span>ggplot_converter</a>
<a class="sourceLine" id="cb7-3" title="3"><span class="co">#> function(plot) {</span></a>
<a class="sourceLine" id="cb7-4" title="4"><span class="co">#> # convert the saved plot</span></a>
<a class="sourceLine" id="cb7-5" title="5"><span class="co">#> p <- cowplot::ggdraw() +</span></a>
<a class="sourceLine" id="cb7-6" title="6"><span class="co">#> cowplot::draw_grob(grid::grobTree(plot))</span></a>
<a class="sourceLine" id="cb7-7" title="7"><span class="co">#> </span></a>
<a class="sourceLine" id="cb7-8" title="8"><span class="co">#> # returning the converted plot</span></a>
<a class="sourceLine" id="cb7-9" title="9"><span class="co">#> return(p)</span></a>
<a class="sourceLine" id="cb7-10" title="10"><span class="co">#> }</span></a>
<a class="sourceLine" id="cb7-11" title="11"><span class="co">#> <bytecode: 0x0000000029b66570></span></a>
<a class="sourceLine" id="cb7-12" title="12"><span class="co">#> <environment: namespace:ggstatsplot></span></a></code></pre></div>
<p>If you are not familiar either with what the namespace <code>::</code> does or how to use pipe operator <code>%>%</code>, something this package and its documentation relies a lot on, you can check out these links-</p>
<ul>
<li><a href="http://r-pkgs.had.co.nz/namespace.html" class="uri">http://r-pkgs.had.co.nz/namespace.html</a></li>
<li><a href="http://r4ds.had.co.nz/pipes.html" class="uri">http://r4ds.had.co.nz/pipes.html</a></li>
</ul>
</div>
<div id="usage" class="section level2">
<h2 class="hasAnchor">
<a href="#usage" class="anchor"></a>Usage</h2>
<p><code>ggstatsplot</code> relies on non-standard evaluation (NSE), i.e., rather than looking at the values of arguments (<code>x</code>, <code>y</code>), it instead looks at their expressions. This means that you <strong>shouldn’t</strong> enter arguments with the <code>$</code> operator and setting <code>data = NULL</code>: <code>data = NULL, x = data$x, y = data$y</code>. You <strong>must</strong> always specify the <code>data</code> argument for all functions. On the plus side, you can enter arguments either as a string (<code>x = "x", y = "y"</code>) or as a bare expression (<code>x = x, y = y</code>) and it wouldn’t matter. To read more about NSE, see- <a href="http://adv-r.had.co.nz/Computing-on-the-language.html" class="uri">http://adv-r.had.co.nz/Computing-on-the-language.html</a></p>
<p><code>ggstatsplot</code> is a very chatty package and will by default print helpful notes on assumptions about linear models, warnings, etc. If you don’t want your console to be cluttered with such messages, they can be turned off by setting argument <code>messages = FALSE</code> in the function call.</p>
<p>Here are examples of the main functions currently supported in <code>ggstatsplot</code>.</p>
<p><strong>Note</strong>: If you are reading this on GitHub repository, the documentation below is for the <strong>development</strong> version of the package. So you may see some features available here that are not currently present in the stable version of this package on <strong>CRAN</strong>. For documentation relevant for the CRAN version, see:</p>
<ul>
<li>vignettes: <a href="https://cran.r-project.org/web/packages/ggstatsplot/vignettes/" class="uri">https://cran.r-project.org/web/packages/ggstatsplot/vignettes/</a>
</li>
<li>README: <a href="https://cran.r-project.org/web/packages/ggstatsplot/readme/README.html" class="uri">https://cran.r-project.org/web/packages/ggstatsplot/readme/README.html</a>
</li>
</ul>
</div>
<div id="ggbetweenstats" class="section level2">
<h2 class="hasAnchor">
<a href="#ggbetweenstats" class="anchor"></a><code>ggbetweenstats</code>
</h2>
<p>This function creates either a violin plot, a box plot, or a mix of two for <strong>between</strong>-group or <strong>between</strong>-condition comparisons with results from statistical tests in the subtitle. The simplest function call looks like this-</p>
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" title="1"><span class="co"># loading needed libraries</span></a>
<a class="sourceLine" id="cb8-2" title="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(ggstatsplot)</a>
<a class="sourceLine" id="cb8-3" title="3"></a>
<a class="sourceLine" id="cb8-4" title="4"><span class="co"># for reproducibility</span></a>
<a class="sourceLine" id="cb8-5" title="5"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/Random">set.seed</a></span>(<span class="dv">123</span>)</a>
<a class="sourceLine" id="cb8-6" title="6"></a>
<a class="sourceLine" id="cb8-7" title="7"><span class="co"># plot</span></a>
<a class="sourceLine" id="cb8-8" title="8">ggstatsplot<span class="op">::</span><span class="kw"><a href="https://indrajeetpatil.github.io/ggstatsplot//reference/ggbetweenstats.html">ggbetweenstats</a></span>(</a>
<a class="sourceLine" id="cb8-9" title="9"> <span class="dt">data =</span> iris,</a>
<a class="sourceLine" id="cb8-10" title="10"> <span class="dt">x =</span> Species,</a>
<a class="sourceLine" id="cb8-11" title="11"> <span class="dt">y =</span> Sepal.Length,</a>
<a class="sourceLine" id="cb8-12" title="12"> <span class="dt">messages =</span> <span class="ot">FALSE</span></a>
<a class="sourceLine" id="cb8-13" title="13">) <span class="op">+</span><span class="st"> </span><span class="co"># further modification outside of ggstatsplot</span></a>
<a class="sourceLine" id="cb8-14" title="14"><span class="st"> </span>ggplot2<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/ggplot2/topics/coord_cartesian">coord_cartesian</a></span>(<span class="dt">ylim =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="dv">3</span>, <span class="dv">8</span>)) <span class="op">+</span></a>
<a class="sourceLine" id="cb8-15" title="15"><span class="st"> </span>ggplot2<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/ggplot2/topics/scale_continuous">scale_y_continuous</a></span>(<span class="dt">breaks =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/seq">seq</a></span>(<span class="dv">3</span>, <span class="dv">8</span>, <span class="dt">by =</span> <span class="dv">1</span>))</a></code></pre></div>
<p><img src="reference/figures/README-ggbetweenstats1-1.png" width="100%"></p>
<p>Note that this function returns a <code>ggplot2</code> object and thus any of the graphics layers can be further modified.</p>
<p>The <code>type</code> (of test) argument also accepts the following abbreviations: <code>"p"</code> (for <em>parametric</em>) or <code>"np"</code> (for <em>nonparametric</em>) or <code>"r"</code> (for <em>robust</em>) or <code>"bf"</code> (for <em>Bayes Factor</em>). Additionally, the type of plot to be displayed can also be modified (<code>"box"</code>, <code>"violin"</code>, or <code>"boxviolin"</code>).</p>
<p>A number of other arguments can be specified to make this plot even more informative or change some of the default options.</p>
<div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb9-1" title="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(ggplot2)</a>
<a class="sourceLine" id="cb9-2" title="2"></a>
<a class="sourceLine" id="cb9-3" title="3"><span class="co"># for reproducibility</span></a>
<a class="sourceLine" id="cb9-4" title="4"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/Random">set.seed</a></span>(<span class="dv">123</span>)</a>
<a class="sourceLine" id="cb9-5" title="5"></a>
<a class="sourceLine" id="cb9-6" title="6"><span class="co"># let's leave out one of the factor levels and see if instead of anova, a t-test will be run</span></a>
<a class="sourceLine" id="cb9-7" title="7">iris2 <-<span class="st"> </span>dplyr<span class="op">::</span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="dt">.data =</span> iris, Species <span class="op">!=</span><span class="st"> "setosa"</span>)</a>
<a class="sourceLine" id="cb9-8" title="8"></a>
<a class="sourceLine" id="cb9-9" title="9"><span class="co"># let's change the levels of our factors, a common routine in data analysis</span></a>
<a class="sourceLine" id="cb9-10" title="10"><span class="co"># pipeline, to see if this function respects the new factor levels</span></a>
<a class="sourceLine" id="cb9-11" title="11">iris2<span class="op">$</span>Species <-</a>
<a class="sourceLine" id="cb9-12" title="12"><span class="st"> </span>base<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/factor">factor</a></span>(</a>
<a class="sourceLine" id="cb9-13" title="13"> <span class="dt">x =</span> iris2<span class="op">$</span>Species,</a>
<a class="sourceLine" id="cb9-14" title="14"> <span class="dt">levels =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"virginica"</span>, <span class="st">"versicolor"</span>)</a>
<a class="sourceLine" id="cb9-15" title="15"> )</a>
<a class="sourceLine" id="cb9-16" title="16"></a>
<a class="sourceLine" id="cb9-17" title="17"><span class="co"># plot</span></a>
<a class="sourceLine" id="cb9-18" title="18">ggstatsplot<span class="op">::</span><span class="kw"><a href="https://indrajeetpatil.github.io/ggstatsplot//reference/ggbetweenstats.html">ggbetweenstats</a></span>(</a>
<a class="sourceLine" id="cb9-19" title="19"> <span class="dt">data =</span> iris2,</a>
<a class="sourceLine" id="cb9-20" title="20"> <span class="dt">x =</span> Species,</a>
<a class="sourceLine" id="cb9-21" title="21"> <span class="dt">y =</span> Sepal.Length,</a>
<a class="sourceLine" id="cb9-22" title="22"> <span class="dt">notch =</span> <span class="ot">TRUE</span>, <span class="co"># show notched box plot</span></a>
<a class="sourceLine" id="cb9-23" title="23"> <span class="dt">mean.plotting =</span> <span class="ot">TRUE</span>, <span class="co"># whether mean for each group is to be displayed</span></a>
<a class="sourceLine" id="cb9-24" title="24"> <span class="dt">mean.ci =</span> <span class="ot">TRUE</span>, <span class="co"># whether to display confidence interval for means</span></a>
<a class="sourceLine" id="cb9-25" title="25"> <span class="dt">mean.label.size =</span> <span class="fl">2.5</span>, <span class="co"># size of the label for mean</span></a>
<a class="sourceLine" id="cb9-26" title="26"> <span class="dt">type =</span> <span class="st">"p"</span>, <span class="co"># which type of test is to be run</span></a>
<a class="sourceLine" id="cb9-27" title="27"> <span class="dt">bf.message =</span> <span class="ot">TRUE</span>, <span class="co"># add a message with bayes factor favoring null</span></a>
<a class="sourceLine" id="cb9-28" title="28"> <span class="dt">k =</span> <span class="dv">3</span>, <span class="co"># number of decimal places for statistical results</span></a>
<a class="sourceLine" id="cb9-29" title="29"> <span class="dt">outlier.tagging =</span> <span class="ot">TRUE</span>, <span class="co"># whether outliers need to be tagged</span></a>
<a class="sourceLine" id="cb9-30" title="30"> <span class="dt">outlier.label =</span> Sepal.Width, <span class="co"># variable to be used for the outlier tag</span></a>
<a class="sourceLine" id="cb9-31" title="31"> <span class="dt">outlier.label.color =</span> <span class="st">"darkgreen"</span>, <span class="co"># changing the color for the text label</span></a>
<a class="sourceLine" id="cb9-32" title="32"> <span class="dt">xlab =</span> <span class="st">"Type of Species"</span>, <span class="co"># label for the x-axis variable</span></a>
<a class="sourceLine" id="cb9-33" title="33"> <span class="dt">ylab =</span> <span class="st">"Attribute: Sepal Length"</span>, <span class="co"># label for the y-axis variable</span></a>
<a class="sourceLine" id="cb9-34" title="34"> <span class="dt">title =</span> <span class="st">"Dataset: Iris flower data set"</span>, <span class="co"># title text for the plot</span></a>
<a class="sourceLine" id="cb9-35" title="35"> <span class="dt">ggtheme =</span> ggthemes<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/ggthemes/topics/theme_fivethirtyeight">theme_fivethirtyeight</a></span>(), <span class="co"># choosing a different theme</span></a>
<a class="sourceLine" id="cb9-36" title="36"> <span class="dt">ggstatsplot.layer =</span> <span class="ot">FALSE</span>, <span class="co"># turn off ggstatsplot theme layer</span></a>
<a class="sourceLine" id="cb9-37" title="37"> <span class="dt">package =</span> <span class="st">"wesanderson"</span>, <span class="co"># package from which color palette is to be taken</span></a>
<a class="sourceLine" id="cb9-38" title="38"> <span class="dt">palette =</span> <span class="st">"Darjeeling1"</span>, <span class="co"># choosing a different color palette</span></a>
<a class="sourceLine" id="cb9-39" title="39"> <span class="dt">messages =</span> <span class="ot">FALSE</span></a>
<a class="sourceLine" id="cb9-40" title="40">)</a></code></pre></div>
<p><img src="reference/figures/README-ggbetweenstats2-1.png" width="100%"></p>
<p>In case of a parametric t-test, setting <code>bf.message = TRUE</code> will also attach results from Bayesian Student’s <em>t</em>-test. That way, if the null hypothesis can’t be rejected with the NHST approach, the Bayesian approach can help index evidence in favor of the null hypothesis (i.e., <code>BF01</code>).</p>
<p>By default, Bayes Factor quantifies the support for the alternative hypothesis (H1) over the null hypothesis (H0) (i.e., <code>BF10</code> is displayed). Natural logarithms are shown because BF values can be pretty large. This also makes it easy to compare evidence in favor alternative (<code>BF10</code>) versus null (<code>BF01</code>) hypotheses (since <code>log(BF10) = - log(BF01)</code>).</p>
<p>Additionally, there is also a <code>grouped_</code> variant of this function that makes it easy to repeat the same operation across a <strong>single</strong> grouping variable:</p>
<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb10-1" title="1"><span class="co"># for reproducibility</span></a>
<a class="sourceLine" id="cb10-2" title="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/Random">set.seed</a></span>(<span class="dv">123</span>)</a>
<a class="sourceLine" id="cb10-3" title="3"></a>
<a class="sourceLine" id="cb10-4" title="4"><span class="co"># plot</span></a>
<a class="sourceLine" id="cb10-5" title="5">ggstatsplot<span class="op">::</span><span class="kw"><a href="https://indrajeetpatil.github.io/ggstatsplot//reference/grouped_ggbetweenstats.html">grouped_ggbetweenstats</a></span>(</a>
<a class="sourceLine" id="cb10-6" title="6"> <span class="dt">data =</span> dplyr<span class="op">::</span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(</a>
<a class="sourceLine" id="cb10-7" title="7"> <span class="dt">.data =</span> ggstatsplot<span class="op">::</span>movies_long,</a>
<a class="sourceLine" id="cb10-8" title="8"> genre <span class="op">%in%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"Action"</span>, <span class="st">"Action Comedy"</span>, <span class="st">"Action Drama"</span>, <span class="st">"Comedy"</span>)</a>
<a class="sourceLine" id="cb10-9" title="9"> ),</a>
<a class="sourceLine" id="cb10-10" title="10"> <span class="dt">x =</span> mpaa,</a>
<a class="sourceLine" id="cb10-11" title="11"> <span class="dt">y =</span> length,</a>
<a class="sourceLine" id="cb10-12" title="12"> <span class="dt">grouping.var =</span> genre, <span class="co"># grouping variable</span></a>
<a class="sourceLine" id="cb10-13" title="13"> <span class="dt">pairwise.comparisons =</span> <span class="ot">TRUE</span>, <span class="co"># display significant pairwise comparisons</span></a>
<a class="sourceLine" id="cb10-14" title="14"> <span class="dt">pairwise.annotation =</span> <span class="st">"p.value"</span>, <span class="co"># how do you want to annotate the pairwise comparisons</span></a>
<a class="sourceLine" id="cb10-15" title="15"> <span class="dt">p.adjust.method =</span> <span class="st">"bonferroni"</span>, <span class="co"># method for adjusting p-values for multiple comparisons</span></a>
<a class="sourceLine" id="cb10-16" title="16"> <span class="dt">bf.message =</span> <span class="ot">TRUE</span>, <span class="co"># display Bayes Factor in favor of the null hypothesis</span></a>
<a class="sourceLine" id="cb10-17" title="17"> <span class="dt">conf.level =</span> <span class="fl">0.99</span>, <span class="co"># changing confidence level to 99%</span></a>
<a class="sourceLine" id="cb10-18" title="18"> <span class="dt">ggplot.component =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/list">list</a></span>( <span class="co"># adding new components to `ggstatsplot` default</span></a>
<a class="sourceLine" id="cb10-19" title="19"> ggplot2<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/ggplot2/topics/scale_continuous">scale_y_continuous</a></span>(<span class="dt">sec.axis =</span> ggplot2<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/ggplot2/topics/sec_axis">dup_axis</a></span>())</a>
<a class="sourceLine" id="cb10-20" title="20"> ),</a>
<a class="sourceLine" id="cb10-21" title="21"> <span class="dt">k =</span> <span class="dv">3</span>,</a>
<a class="sourceLine" id="cb10-22" title="22"> <span class="dt">title.prefix =</span> <span class="st">"Movie genre"</span>,</a>
<a class="sourceLine" id="cb10-23" title="23"> <span class="dt">caption =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/substitute">substitute</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/paste">paste</a></span>(</a>
<a class="sourceLine" id="cb10-24" title="24"> <span class="kw"><a href="https://www.rdocumentation.org/packages/grDevices/topics/plotmath">italic</a></span>(<span class="st">"Source"</span>),</a>
<a class="sourceLine" id="cb10-25" title="25"> <span class="st">":IMDb (Internet Movie Database)"</span></a>
<a class="sourceLine" id="cb10-26" title="26"> )),</a>
<a class="sourceLine" id="cb10-27" title="27"> <span class="dt">palette =</span> <span class="st">"default_jama"</span>,</a>
<a class="sourceLine" id="cb10-28" title="28"> <span class="dt">package =</span> <span class="st">"ggsci"</span>,</a>
<a class="sourceLine" id="cb10-29" title="29"> <span class="dt">messages =</span> <span class="ot">FALSE</span>,</a>
<a class="sourceLine" id="cb10-30" title="30"> <span class="dt">nrow =</span> <span class="dv">2</span>,</a>
<a class="sourceLine" id="cb10-31" title="31"> <span class="dt">title.text =</span> <span class="st">"Differences in movie length by mpaa ratings for different genres"</span></a>
<a class="sourceLine" id="cb10-32" title="32">)</a></code></pre></div>
<p><img src="reference/figures/README-ggbetweenstats3-1.png" width="100%"></p>
<div id="summary-of-tests" class="section level3">
<h3 class="hasAnchor">
<a href="#summary-of-tests" class="anchor"></a>Summary of tests</h3>
<p>Following (between-subjects) tests are carried out for each type of analyses-</p>
<table class="table table">
<thead><tr class="header">
<th>Type</th>
<th>No. of groups</th>
<th>Test</th>
</tr></thead>
<tbody>
<tr class="odd">
<td>Parametric</td>
<td>> 2</td>
<td>Student’s or Welch’s one-way ANOVA</td>
</tr>
<tr class="even">
<td>Non-parametric</td>
<td>> 2</td>
<td>Kruskal–Wallis one-way ANOVA</td>
</tr>
<tr class="odd">
<td>Robust</td>
<td>> 2</td>
<td>Heteroscedastic one-way ANOVA for trimmed means</td>
</tr>
<tr class="even">
<td>Bayes Factor</td>
<td>> 2</td>
<td>Student’s ANOVA</td>
</tr>
<tr class="odd">
<td>Parametric</td>
<td>2</td>
<td>Student’s or Welch’s <em>t</em>-test</td>
</tr>
<tr class="even">
<td>Non-parametric</td>
<td>2</td>
<td>Mann–Whitney <em>U</em> test</td>
</tr>
<tr class="odd">
<td>Robust</td>
<td>2</td>
<td>Yuen’s test for trimmed means</td>
</tr>
<tr class="even">
<td>Bayes Factor</td>
<td>2</td>
<td>Student’s <em>t</em>-test</td>
</tr>
</tbody>
</table>
<p>Here is a summary of <em>multiple pairwise comparison</em> tests supported in <em>ggbetweenstats</em>-</p>
<table class="table table">
<thead><tr class="header">
<th>Type</th>
<th>Equal variance?</th>
<th>Test</th>
<th>
<em>p</em>-value adjustment?</th>
</tr></thead>
<tbody>
<tr class="odd">
<td>Parametric</td>
<td>No</td>
<td>Games-Howell test</td>
<td><font color="green">Yes</font></td>
</tr>
<tr class="even">
<td>Parametric</td>
<td>Yes</td>
<td>Student’s <em>t</em>-test</td>
<td><font color="green">Yes</font></td>
</tr>
<tr class="odd">
<td>Non-parametric</td>
<td>No</td>
<td>Dwass-Steel-Crichtlow-Fligner test</td>
<td><font color="green">Yes</font></td>
</tr>
<tr class="even">
<td>Robust</td>
<td>No</td>
<td>Yuen’s trimmed means test</td>
<td><font color="green">Yes</font></td>
</tr>
<tr class="odd">
<td>Bayes Factor</td>
<td>No</td>
<td><font color="red">No</font></td>
<td><font color="red">No</font></td>
</tr>
<tr class="even">
<td>Bayes Factor</td>
<td>Yes</td>
<td><font color="red">No</font></td>
<td><font color="red">No</font></td>
</tr>
</tbody>
</table>
<p>For more, see the <code>ggbetweenstats</code> vignette: <a href="https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggbetweenstats.html" class="uri">https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggbetweenstats.html</a></p>
</div>
</div>
<div id="ggwithinstats" class="section level2">
<h2 class="hasAnchor">
<a href="#ggwithinstats" class="anchor"></a><code>ggwithinstats</code>
</h2>
<p><code>ggbetweenstats</code> function has an identical twin function <code>ggwithinstats</code> for repeated measures designs that behaves in the same fashion with few minor tweaks. As can be seen from an example below, the only difference between the plot structure is that now the group means are connected by paths to highlight the within-subjects nature of the data.</p>
<div class="sourceCode" id="cb11"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb11-1" title="1"><span class="co"># for reproducibility and data</span></a>
<a class="sourceLine" id="cb11-2" title="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/Random">set.seed</a></span>(<span class="dv">123</span>)</a>
<a class="sourceLine" id="cb11-3" title="3"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(WRS2)</a>
<a class="sourceLine" id="cb11-4" title="4"></a>
<a class="sourceLine" id="cb11-5" title="5"><span class="co"># plot</span></a>
<a class="sourceLine" id="cb11-6" title="6">ggstatsplot<span class="op">::</span><span class="kw"><a href="https://indrajeetpatil.github.io/ggstatsplot//reference/ggwithinstats.html">ggwithinstats</a></span>(</a>
<a class="sourceLine" id="cb11-7" title="7"> <span class="dt">data =</span> WRS2<span class="op">::</span>WineTasting,</a>
<a class="sourceLine" id="cb11-8" title="8"> <span class="dt">x =</span> Wine,</a>
<a class="sourceLine" id="cb11-9" title="9"> <span class="dt">y =</span> Taste,</a>
<a class="sourceLine" id="cb11-10" title="10"> <span class="dt">sort =</span> <span class="st">"descending"</span>, <span class="co"># ordering groups along the x-axis based on</span></a>
<a class="sourceLine" id="cb11-11" title="11"> <span class="dt">sort.fun =</span> median, <span class="co"># values of `y` variable</span></a>
<a class="sourceLine" id="cb11-12" title="12"> <span class="dt">pairwise.comparisons =</span> <span class="ot">TRUE</span>,</a>
<a class="sourceLine" id="cb11-13" title="13"> <span class="dt">pairwise.display =</span> <span class="st">"s"</span>,</a>
<a class="sourceLine" id="cb11-14" title="14"> <span class="dt">pairwise.annotation =</span> <span class="st">"p"</span>,</a>
<a class="sourceLine" id="cb11-15" title="15"> <span class="dt">title =</span> <span class="st">"Wine tasting"</span>,</a>
<a class="sourceLine" id="cb11-16" title="16"> <span class="dt">caption =</span> <span class="st">"Source: `WRS2` R package"</span>,</a>
<a class="sourceLine" id="cb11-17" title="17"> <span class="dt">ggtheme =</span> ggthemes<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/ggthemes/topics/theme_fivethirtyeight">theme_fivethirtyeight</a></span>(),</a>
<a class="sourceLine" id="cb11-18" title="18"> <span class="dt">ggstatsplot.layer =</span> <span class="ot">FALSE</span>,</a>
<a class="sourceLine" id="cb11-19" title="19"> <span class="dt">messages =</span> <span class="ot">FALSE</span></a>
<a class="sourceLine" id="cb11-20" title="20">)</a></code></pre></div>
<p><img src="reference/figures/README-ggwithinstats1-1.png" width="100%"></p>
<p>As with the <code>ggbetweenstats</code>, this function also has a <code>grouped_</code> variant that makes repeating the same analysis across a single grouping variable quicker. We will see an example with only repeated measurements-</p>
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb12-1" title="1"><span class="co"># common setup</span></a>
<a class="sourceLine" id="cb12-2" title="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/Random">set.seed</a></span>(<span class="dv">123</span>)</a>
<a class="sourceLine" id="cb12-3" title="3"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(jmv)</a>
<a class="sourceLine" id="cb12-4" title="4"><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/data">data</a></span>(<span class="st">"bugs"</span>, <span class="dt">package =</span> <span class="st">"jmv"</span>)</a>
<a class="sourceLine" id="cb12-5" title="5"></a>
<a class="sourceLine" id="cb12-6" title="6"><span class="co"># getting data in tidy format</span></a>
<a class="sourceLine" id="cb12-7" title="7">data_bugs <-<span class="st"> </span>bugs <span class="op">%>%</span></a>
<a class="sourceLine" id="cb12-8" title="8"><span class="st"> </span>tibble<span class="op">::</span><span class="kw"><a href="https://tibble.tidyverse.org/reference/as_tibble.html">as_tibble</a></span>(<span class="dt">x =</span> .) <span class="op">%>%</span></a>
<a class="sourceLine" id="cb12-9" title="9"><span class="st"> </span>tidyr<span class="op">::</span><span class="kw"><a href="https://tidyr.tidyverse.org/reference/gather.html">gather</a></span>(<span class="dt">data =</span> ., key, value, LDLF<span class="op">:</span>HDHF) <span class="op">%>%</span></a>
<a class="sourceLine" id="cb12-10" title="10"><span class="st"> </span>dplyr<span class="op">::</span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="dt">.data =</span> ., Region <span class="op">%in%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"Europe"</span>, <span class="st">"North America"</span>))</a>
<a class="sourceLine" id="cb12-11" title="11"></a>
<a class="sourceLine" id="cb12-12" title="12"><span class="co"># plot</span></a>
<a class="sourceLine" id="cb12-13" title="13">ggstatsplot<span class="op">::</span><span class="kw"><a href="https://indrajeetpatil.github.io/ggstatsplot//reference/grouped_ggwithinstats.html">grouped_ggwithinstats</a></span>(</a>
<a class="sourceLine" id="cb12-14" title="14"> <span class="dt">data =</span> dplyr<span class="op">::</span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(data_bugs, key <span class="op">%in%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"LDLF"</span>, <span class="st">"LDHF"</span>)),</a>
<a class="sourceLine" id="cb12-15" title="15"> <span class="dt">x =</span> key,</a>
<a class="sourceLine" id="cb12-16" title="16"> <span class="dt">y =</span> value,</a>
<a class="sourceLine" id="cb12-17" title="17"> <span class="dt">xlab =</span> <span class="st">"Condition"</span>,</a>
<a class="sourceLine" id="cb12-18" title="18"> <span class="dt">ylab =</span> <span class="st">"Desire to kill an artrhopod"</span>,</a>
<a class="sourceLine" id="cb12-19" title="19"> <span class="dt">grouping.var =</span> Region,</a>
<a class="sourceLine" id="cb12-20" title="20"> <span class="dt">outlier.tagging =</span> <span class="ot">TRUE</span>,</a>
<a class="sourceLine" id="cb12-21" title="21"> <span class="dt">outlier.label =</span> Education,</a>
<a class="sourceLine" id="cb12-22" title="22"> <span class="dt">bf.message =</span> <span class="ot">TRUE</span>,</a>
<a class="sourceLine" id="cb12-23" title="23"> <span class="dt">ggtheme =</span> hrbrthemes<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/hrbrthemes/topics/theme_ipsum_tw">theme_ipsum_tw</a></span>(),</a>
<a class="sourceLine" id="cb12-24" title="24"> <span class="dt">ggstatsplot.layer =</span> <span class="ot">FALSE</span>,</a>
<a class="sourceLine" id="cb12-25" title="25"> <span class="dt">messages =</span> <span class="ot">FALSE</span></a>
<a class="sourceLine" id="cb12-26" title="26">)</a></code></pre></div>
<p><img src="reference/figures/README-ggwithinstats2-1.png" width="100%"></p>
<div id="summary-of-tests-1" class="section level3">
<h3 class="hasAnchor">
<a href="#summary-of-tests-1" class="anchor"></a>Summary of tests</h3>
<p>Following (within-subjects) tests are carried out for each type of analyses-</p>
<table class="table table">
<colgroup>
<col width="28%">
<col width="7%">
<col width="64%">
</colgroup>
<thead><tr class="header">
<th>Type</th>
<th>No. of groups</th>
<th>Test</th>
</tr></thead>
<tbody>
<tr class="odd">
<td>Parametric</td>
<td>> 2</td>
<td>One-way repeated measures ANOVA</td>
</tr>
<tr class="even">
<td>Non-parametric</td>
<td>> 2</td>
<td>Friedman test</td>
</tr>
<tr class="odd">
<td>Robust</td>
<td>> 2</td>
<td>Heteroscedastic one-way repeated measures ANOVA for trimmed means</td>
</tr>
<tr class="even">
<td>Bayes Factor</td>
<td>> 2</td>
<td>One-way repeated measures ANOVA</td>
</tr>
<tr class="odd">
<td>Parametric</td>
<td>2</td>
<td>Student’s <em>t</em>-test</td>
</tr>
<tr class="even">
<td>Non-parametric</td>
<td>2</td>
<td>Mann–Whitney <em>U</em> test</td>
</tr>
<tr class="odd">
<td>Robust</td>
<td>2</td>
<td>Yuen’s test on trimmed means for dependent samples</td>
</tr>
<tr class="even">
<td>Bayes Factor</td>
<td>2</td>
<td>Student’s <em>t</em>-test</td>
</tr>
</tbody>
</table>
<p>Here is a summary of <em>multiple pairwise comparison</em> tests supported in <em>ggwithinstats</em>-</p>
<table class="table table">
<thead><tr class="header">
<th>Type</th>
<th>Test</th>
<th>
<em>p</em>-value adjustment?</th>
</tr></thead>
<tbody>
<tr class="odd">
<td>Parametric</td>
<td>Student’s <em>t</em>-test</td>
<td><font color="green">Yes</font></td>
</tr>
<tr class="even">
<td>Non-parametric</td>
<td>Durbin-Conover test</td>
<td><font color="green">Yes</font></td>
</tr>
<tr class="odd">
<td>Robust</td>
<td>Yuen’s trimmed means test</td>
<td><font color="green">Yes</font></td>
</tr>
<tr class="even">
<td>Bayes Factor</td>
<td><font color="red">No</font></td>
<td><font color="red">No</font></td>
</tr>
</tbody>
</table>
<p>For more, see the <code>ggbetweenstats</code> vignette: <a href="https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggwithinstats.html" class="uri">https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggwithinstats.html</a></p>
</div>
</div>
<div id="ggscatterstats" class="section level2">
<h2 class="hasAnchor">
<a href="#ggscatterstats" class="anchor"></a><code>ggscatterstats</code>
</h2>
<p>This function creates a scatterplot with marginal histograms/boxplots/density/violin/densigram plots from <code><a href="https://www.rdocumentation.org/packages/ggExtra/topics/ggMarginal">ggExtra::ggMarginal</a></code> and results from statistical tests in the subtitle:</p>
<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" title="1">ggstatsplot<span class="op">::</span><span class="kw"><a href="https://indrajeetpatil.github.io/ggstatsplot//reference/ggscatterstats.html">ggscatterstats</a></span>(</a>
<a class="sourceLine" id="cb13-2" title="2"> <span class="dt">data =</span> ggplot2<span class="op">::</span>msleep,</a>
<a class="sourceLine" id="cb13-3" title="3"> <span class="dt">x =</span> sleep_rem,</a>
<a class="sourceLine" id="cb13-4" title="4"> <span class="dt">y =</span> awake,</a>
<a class="sourceLine" id="cb13-5" title="5"> <span class="dt">xlab =</span> <span class="st">"REM sleep (in hours)"</span>,</a>
<a class="sourceLine" id="cb13-6" title="6"> <span class="dt">ylab =</span> <span class="st">"Amount of time spent awake (in hours)"</span>,</a>
<a class="sourceLine" id="cb13-7" title="7"> <span class="dt">title =</span> <span class="st">"Understanding mammalian sleep"</span>,</a>
<a class="sourceLine" id="cb13-8" title="8"> <span class="dt">bf.message =</span> <span class="ot">TRUE</span>,</a>
<a class="sourceLine" id="cb13-9" title="9"> <span class="dt">messages =</span> <span class="ot">FALSE</span></a>
<a class="sourceLine" id="cb13-10" title="10">)</a></code></pre></div>
<p><img src="reference/figures/README-ggscatterstats1-1.png" width="100%"></p>
<p>Number of other arguments can be specified to modify this basic plot-</p>
<div class="sourceCode" id="cb14"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb14-1" title="1"><span class="co"># for reproducibility</span></a>
<a class="sourceLine" id="cb14-2" title="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/Random">set.seed</a></span>(<span class="dv">123</span>)</a>
<a class="sourceLine" id="cb14-3" title="3"></a>
<a class="sourceLine" id="cb14-4" title="4"><span class="co"># plot</span></a>
<a class="sourceLine" id="cb14-5" title="5">ggstatsplot<span class="op">::</span><span class="kw"><a href="https://indrajeetpatil.github.io/ggstatsplot//reference/ggscatterstats.html">ggscatterstats</a></span>(</a>
<a class="sourceLine" id="cb14-6" title="6"> <span class="dt">data =</span> dplyr<span class="op">::</span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(<span class="dt">.data =</span> ggstatsplot<span class="op">::</span>movies_long, genre <span class="op">==</span><span class="st"> "Action"</span>),</a>
<a class="sourceLine" id="cb14-7" title="7"> <span class="dt">x =</span> budget,</a>
<a class="sourceLine" id="cb14-8" title="8"> <span class="dt">y =</span> rating,</a>
<a class="sourceLine" id="cb14-9" title="9"> <span class="dt">type =</span> <span class="st">"robust"</span>, <span class="co"># type of test that needs to be run</span></a>
<a class="sourceLine" id="cb14-10" title="10"> <span class="dt">conf.level =</span> <span class="fl">0.99</span>, <span class="co"># confidence level</span></a>
<a class="sourceLine" id="cb14-11" title="11"> <span class="dt">xlab =</span> <span class="st">"Movie budget (in million/ US$)"</span>, <span class="co"># label for x axis</span></a>
<a class="sourceLine" id="cb14-12" title="12"> <span class="dt">ylab =</span> <span class="st">"IMDB rating"</span>, <span class="co"># label for y axis</span></a>
<a class="sourceLine" id="cb14-13" title="13"> <span class="dt">label.var =</span> <span class="st">"title"</span>, <span class="co"># variable for labeling data points</span></a>
<a class="sourceLine" id="cb14-14" title="14"> <span class="dt">label.expression =</span> <span class="st">"rating < 5 & budget > 150"</span>, <span class="co"># expression that decides which points to label</span></a>
<a class="sourceLine" id="cb14-15" title="15"> <span class="dt">line.color =</span> <span class="st">"yellow"</span>, <span class="co"># changing regression line color line</span></a>
<a class="sourceLine" id="cb14-16" title="16"> <span class="dt">title =</span> <span class="st">"Movie budget and IMDB rating (action)"</span>, <span class="co"># title text for the plot</span></a>
<a class="sourceLine" id="cb14-17" title="17"> <span class="dt">caption =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/expression">expression</a></span>( <span class="co"># caption text for the plot</span></a>
<a class="sourceLine" id="cb14-18" title="18"> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/paste">paste</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/grDevices/topics/plotmath">italic</a></span>(<span class="st">"Note"</span>), <span class="st">": IMDB stands for Internet Movie DataBase"</span>)</a>
<a class="sourceLine" id="cb14-19" title="19"> ),</a>
<a class="sourceLine" id="cb14-20" title="20"> <span class="dt">ggtheme =</span> hrbrthemes<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/hrbrthemes/topics/theme_ipsum_ps">theme_ipsum_ps</a></span>(), <span class="co"># choosing a different theme</span></a>
<a class="sourceLine" id="cb14-21" title="21"> <span class="dt">ggstatsplot.layer =</span> <span class="ot">FALSE</span>, <span class="co"># turn off ggstatsplot theme layer</span></a>
<a class="sourceLine" id="cb14-22" title="22"> <span class="dt">marginal.type =</span> <span class="st">"density"</span>, <span class="co"># type of marginal distribution to be displayed</span></a>
<a class="sourceLine" id="cb14-23" title="23"> <span class="dt">xfill =</span> <span class="st">"#0072B2"</span>, <span class="co"># color fill for x-axis marginal distribution</span></a>
<a class="sourceLine" id="cb14-24" title="24"> <span class="dt">yfill =</span> <span class="st">"#009E73"</span>, <span class="co"># color fill for y-axis marginal distribution</span></a>
<a class="sourceLine" id="cb14-25" title="25"> <span class="dt">xalpha =</span> <span class="fl">0.6</span>, <span class="co"># transparency for x-axis marginal distribution</span></a>
<a class="sourceLine" id="cb14-26" title="26"> <span class="dt">yalpha =</span> <span class="fl">0.6</span>, <span class="co"># transparency for y-axis marginal distribution</span></a>
<a class="sourceLine" id="cb14-27" title="27"> <span class="dt">centrality.para =</span> <span class="st">"median"</span>, <span class="co"># central tendency lines to be displayed</span></a>
<a class="sourceLine" id="cb14-28" title="28"> <span class="dt">point.width.jitter =</span> <span class="fl">0.2</span>, <span class="co"># amount of horizontal jitter for data points</span></a>
<a class="sourceLine" id="cb14-29" title="29"> <span class="dt">point.height.jitter =</span> <span class="fl">0.4</span>, <span class="co"># amount of vertical jitter for data points</span></a>
<a class="sourceLine" id="cb14-30" title="30"> <span class="dt">messages =</span> <span class="ot">FALSE</span> <span class="co"># turn off messages and notes</span></a>
<a class="sourceLine" id="cb14-31" title="31">)</a></code></pre></div>
<p><img src="reference/figures/README-ggscatterstats2-1.png" width="100%"></p>
<p>Additionally, there is also a <code>grouped_</code> variant of this function that makes it easy to repeat the same operation across a <strong>single</strong> grouping variable:</p>
<div class="sourceCode" id="cb15"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb15-1" title="1"><span class="co"># for reproducibility</span></a>
<a class="sourceLine" id="cb15-2" title="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/Random">set.seed</a></span>(<span class="dv">123</span>)</a>
<a class="sourceLine" id="cb15-3" title="3"></a>
<a class="sourceLine" id="cb15-4" title="4"><span class="co"># plot</span></a>
<a class="sourceLine" id="cb15-5" title="5">ggstatsplot<span class="op">::</span><span class="kw"><a href="https://indrajeetpatil.github.io/ggstatsplot//reference/grouped_ggscatterstats.html">grouped_ggscatterstats</a></span>(</a>
<a class="sourceLine" id="cb15-6" title="6"> <span class="dt">data =</span> dplyr<span class="op">::</span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(</a>
<a class="sourceLine" id="cb15-7" title="7"> <span class="dt">.data =</span> ggstatsplot<span class="op">::</span>movies_long,</a>
<a class="sourceLine" id="cb15-8" title="8"> genre <span class="op">%in%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"Action"</span>, <span class="st">"Action Comedy"</span>, <span class="st">"Action Drama"</span>, <span class="st">"Comedy"</span>)</a>
<a class="sourceLine" id="cb15-9" title="9"> ),</a>
<a class="sourceLine" id="cb15-10" title="10"> <span class="dt">x =</span> rating,</a>
<a class="sourceLine" id="cb15-11" title="11"> <span class="dt">y =</span> length,</a>
<a class="sourceLine" id="cb15-12" title="12"> <span class="dt">bf.message =</span> <span class="ot">TRUE</span>, <span class="co"># display bayes factor message</span></a>
<a class="sourceLine" id="cb15-13" title="13"> <span class="dt">conf.level =</span> <span class="fl">0.99</span>,</a>
<a class="sourceLine" id="cb15-14" title="14"> <span class="dt">k =</span> <span class="dv">3</span>, <span class="co"># no. of decimal places in the results</span></a>
<a class="sourceLine" id="cb15-15" title="15"> <span class="dt">xfill =</span> <span class="st">"#E69F00"</span>,</a>
<a class="sourceLine" id="cb15-16" title="16"> <span class="dt">yfill =</span> <span class="st">"#8b3058"</span>,</a>
<a class="sourceLine" id="cb15-17" title="17"> <span class="dt">xlab =</span> <span class="st">"IMDB rating"</span>,</a>
<a class="sourceLine" id="cb15-18" title="18"> <span class="dt">grouping.var =</span> genre, <span class="co"># grouping variable</span></a>
<a class="sourceLine" id="cb15-19" title="19"> <span class="dt">title.prefix =</span> <span class="st">"Movie genre"</span>,</a>
<a class="sourceLine" id="cb15-20" title="20"> <span class="dt">ggtheme =</span> ggplot2<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/ggplot2/topics/ggtheme">theme_grey</a></span>(),</a>
<a class="sourceLine" id="cb15-21" title="21"> <span class="dt">ggplot.component =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/list">list</a></span>(</a>
<a class="sourceLine" id="cb15-22" title="22"> ggplot2<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/ggplot2/topics/scale_continuous">scale_x_continuous</a></span>(<span class="dt">breaks =</span> <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/seq">seq</a></span>(<span class="dv">2</span>, <span class="dv">9</span>, <span class="dv">1</span>), <span class="dt">limits =</span> (<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="dv">2</span>, <span class="dv">9</span>)))</a>
<a class="sourceLine" id="cb15-23" title="23"> ),</a>
<a class="sourceLine" id="cb15-24" title="24"> <span class="dt">messages =</span> <span class="ot">FALSE</span>,</a>
<a class="sourceLine" id="cb15-25" title="25"> <span class="dt">nrow =</span> <span class="dv">2</span>,</a>
<a class="sourceLine" id="cb15-26" title="26"> <span class="dt">ncol =</span> <span class="dv">2</span>,</a>
<a class="sourceLine" id="cb15-27" title="27"> <span class="dt">title.text =</span> <span class="st">"Relationship between movie length by IMDB ratings for different genres"</span></a>
<a class="sourceLine" id="cb15-28" title="28">)</a></code></pre></div>
<p><img src="reference/figures/README-ggscatterstats3-1.png" width="100%"></p>
<div id="summary-of-tests-2" class="section level3">
<h3 class="hasAnchor">
<a href="#summary-of-tests-2" class="anchor"></a>Summary of tests</h3>
<p>Following tests are carried out for each type of analyses. Additionally, the correlation coefficients (and their confidence intervals) are used as effect sizes-</p>
<table class="table table">
<thead><tr class="header">
<th>Type</th>
<th>Test</th>
<th>CI?</th>
</tr></thead>
<tbody>
<tr class="odd">
<td>Parametric</td>
<td>Pearson’s correlation coefficient</td>
<td><font color="green">Yes<font></font></font></td>
</tr>
<tr class="even">
<td>Non-parametric</td>
<td>Spearman’s rank correlation coefficient</td>
<td><font color="green">Yes<font></font></font></td>
</tr>
<tr class="odd">
<td>Robust</td>
<td>Percentage bend correlation coefficient</td>
<td><font color="green">Yes<font></font></font></td>
</tr>
<tr class="even">
<td>Bayes Factor</td>
<td>Pearson’s correlation coefficient</td>
<td><font color="red">No<font></font></font></td>
</tr>
</tbody>
</table>
<p>For more, see the <code>ggscatterstats</code> vignette: <a href="https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggscatterstats.html" class="uri">https://indrajeetpatil.github.io/ggstatsplot/articles/web_only/ggscatterstats.html</a></p>
</div>
</div>
<div id="ggpiestats" class="section level2">
<h2 class="hasAnchor">
<a href="#ggpiestats" class="anchor"></a><code>ggpiestats</code>
</h2>
<p>This function creates a pie chart for categorical or nominal variables with results from contingency table analysis (Pearson’s chi-squared test for between-subjects design and McNemar’s test for within-subjects design) included in the subtitle of the plot. If only one categorical variable is entered, results from one-sample <strong>proportion test</strong> will be displayed as a subtitle.</p>
<div class="sourceCode" id="cb16"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb16-1" title="1"><span class="co"># for reproducibility</span></a>
<a class="sourceLine" id="cb16-2" title="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/Random">set.seed</a></span>(<span class="dv">123</span>)</a>
<a class="sourceLine" id="cb16-3" title="3"></a>
<a class="sourceLine" id="cb16-4" title="4"><span class="co"># plot</span></a>
<a class="sourceLine" id="cb16-5" title="5">ggstatsplot<span class="op">::</span><span class="kw"><a href="https://indrajeetpatil.github.io/ggstatsplot//reference/ggpiestats.html">ggpiestats</a></span>(</a>
<a class="sourceLine" id="cb16-6" title="6"> <span class="dt">data =</span> ggplot2<span class="op">::</span>msleep,</a>
<a class="sourceLine" id="cb16-7" title="7"> <span class="dt">main =</span> vore,</a>
<a class="sourceLine" id="cb16-8" title="8"> <span class="dt">title =</span> <span class="st">"Composition of vore types among mammals"</span>,</a>
<a class="sourceLine" id="cb16-9" title="9"> <span class="dt">messages =</span> <span class="ot">FALSE</span></a>
<a class="sourceLine" id="cb16-10" title="10">)</a></code></pre></div>
<p><img src="reference/figures/README-ggpiestats1-1.png" width="100%"></p>
<p>This function can also be used to study an interaction between two categorical variables. Additionally, this basic plot can further be modified with additional arguments and the function returns a <code>ggplot2</code> object that can further be modified with <code>ggplot2</code> syntax:</p>
<div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" title="1"><span class="co"># for reproducibility</span></a>
<a class="sourceLine" id="cb17-2" title="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/Random">set.seed</a></span>(<span class="dv">123</span>)</a>
<a class="sourceLine" id="cb17-3" title="3"></a>