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<img src="logo.png" class="logo" alt=""><h1 id="jlmerclusterperm-">jlmerclusterperm
<a class="anchor" aria-label="anchor" href="#jlmerclusterperm-"></a>
</h1>
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<p>Julia <a href="https://github.com/JuliaStats/GLM.jl" class="external-link">GLM.jl</a> and <a href="https://github.com/JuliaStats/MixedModels.jl" class="external-link">MixedModels.jl</a> based implementation of the cluster-based permutation test for time series data, powered by <a href="https://github.com/stefan-m-lenz/JuliaConnectoR" class="external-link">JuliaConnectoR</a>.</p>
<p><img src="reference/figures/clusterpermute_slice.png"></p>
<div class="section level2">
<h2 id="installation-and-usage">Installation and usage<a class="anchor" aria-label="anchor" href="#installation-and-usage"></a>
</h2>
<p>Install the released version of jlmerclusterperm from CRAN:</p>
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"jlmerclusterperm"</span><span class="op">)</span></span></code></pre></div>
<p>Or install the development version from <a href="https://github.com/yjunechoe/jlmerclusterperm" class="external-link">GitHub</a> with:</p>
<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="co"># install.packages("remotes")</span></span>
<span><span class="fu">remotes</span><span class="fu">::</span><span class="fu"><a href="https://remotes.r-lib.org/reference/install_github.html" class="external-link">install_github</a></span><span class="op">(</span><span class="st">"yjunechoe/jlmerclusterperm"</span><span class="op">)</span></span></code></pre></div>
<p>Using <code>jlmerclusterperm</code> requires a prior installation of the Julia programming language, which can be downloaded from either the <a href="https://julialang.org/" class="external-link">official website</a> or using the command line utility <a href="https://github.com/JuliaLang/juliaup" class="external-link">juliaup</a>. Julia version >=1.8 is required and <a href="https://julialang.org/blog/2023/04/julia-1.9-highlights/#caching_of_native_code" class="external-link">1.9</a> or higher is preferred for the substantial speed improvements.</p>
<p>Before using functions from <code>jlmerclusterperm</code>, an initial setup is required via calling <code><a href="reference/jlmerclusterperm_setup.html">jlmerclusterperm_setup()</a></code>. The very first call on a system will install necessary dependencies (this only happens once and takes around 10-15 minutes).</p>
<p>Subsequent calls to <code><a href="reference/jlmerclusterperm_setup.html">jlmerclusterperm_setup()</a></code> incur a small overhead of around 30 seconds, plus slight delays for first-time function calls. You pay up front for start-up and warm-up costs and get blazingly-fast functions from the package.</p>
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="co"># Both lines must be run at the start of each new session</span></span>
<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://github.com/yjunechoe/jlmerclusterperm" class="external-link">jlmerclusterperm</a></span><span class="op">)</span></span>
<span><span class="fu"><a href="reference/jlmerclusterperm_setup.html">jlmerclusterperm_setup</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
<p><picture><source media="(prefers-color-scheme: dark)" srcset="man/figures/README-/setup-io-dark.svg"><img src="reference/figures/README-/setup-io.svg" style="display: block; margin: auto;"></source></picture></p>
<p>See the <a href="https://yjunechoe.github.io/jlmerclusterperm/articles/jlmerclusterperm.html">Get Started</a> page on the <a href="https://yjunechoe.github.io/jlmerclusterperm/">package website</a> for background and tutorials.</p>
</div>
<div class="section level2">
<h2 id="quick-tour-of-package-functionalities">Quick tour of package functionalities<a class="anchor" aria-label="anchor" href="#quick-tour-of-package-functionalities"></a>
</h2>
<div class="section level3">
<h3 id="wholesale-cpa-with-clusterpermute">Wholesale CPA with <code>clusterpermute()</code>
<a class="anchor" aria-label="anchor" href="#wholesale-cpa-with-clusterpermute"></a>
</h3>
<p>A time series data:</p>
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">chickweights</span> <span class="op"><-</span> <span class="va">ChickWeight</span></span>
<span><span class="va">chickweights</span><span class="op">$</span><span class="va">Time</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/integer.html" class="external-link">as.integer</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/factor.html" class="external-link">factor</a></span><span class="op">(</span><span class="va">chickweights</span><span class="op">$</span><span class="va">Time</span><span class="op">)</span><span class="op">)</span></span>
<span><span class="fu"><a href="https://rdrr.io/r/graphics/matplot.html" class="external-link">matplot</a></span><span class="op">(</span></span>
<span> <span class="fu"><a href="https://rdrr.io/r/base/tapply.html" class="external-link">tapply</a></span><span class="op">(</span><span class="va">chickweights</span><span class="op">$</span><span class="va">weight</span>, <span class="va">chickweights</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Time"</span>, <span class="st">"Diet"</span><span class="op">)</span><span class="op">]</span>, <span class="va">mean</span><span class="op">)</span>,</span>
<span> type <span class="op">=</span> <span class="st">"b"</span>, lwd <span class="op">=</span> <span class="fl">3</span>, ylab <span class="op">=</span> <span class="st">"Weight"</span>, xlab <span class="op">=</span> <span class="st">"Time"</span></span>
<span><span class="op">)</span></span></code></pre></div>
<p><img src="reference/figures/README-chickweight-1.png" width="75%" style="display: block; margin: auto;"></p>
<p>Preparing a specification object with <code><a href="reference/make_jlmer_spec.html">make_jlmer_spec()</a></code>:</p>
<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">chickweights_spec</span> <span class="op"><-</span> <span class="fu"><a href="reference/make_jlmer_spec.html">make_jlmer_spec</a></span><span class="op">(</span></span>
<span> formula <span class="op">=</span> <span class="va">weight</span> <span class="op">~</span> <span class="fl">1</span> <span class="op">+</span> <span class="va">Diet</span>,</span>
<span> data <span class="op">=</span> <span class="va">chickweights</span>,</span>
<span> subject <span class="op">=</span> <span class="st">"Chick"</span>, time <span class="op">=</span> <span class="st">"Time"</span></span>
<span><span class="op">)</span></span>
<span><span class="va">chickweights_spec</span></span></code></pre></div>
<p><picture><source media="(prefers-color-scheme: dark)" srcset="man/figures/README-/spec-io-dark.svg"><img src="reference/figures/README-/spec-io.svg" style="display: block; margin: auto;"></source></picture></p>
<p>Cluster-based permutation test with <code><a href="reference/clusterpermute.html">clusterpermute()</a></code>:</p>
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="reference/julia_rng.html">set_rng_state</a></span><span class="op">(</span><span class="fl">123L</span><span class="op">)</span></span>
<span><span class="fu"><a href="reference/clusterpermute.html">clusterpermute</a></span><span class="op">(</span></span>
<span> <span class="va">chickweights_spec</span>,</span>
<span> threshold <span class="op">=</span> <span class="fl">2.5</span>,</span>
<span> nsim <span class="op">=</span> <span class="fl">100</span></span>
<span><span class="op">)</span></span></code></pre></div>
<p><picture><source media="(prefers-color-scheme: dark)" srcset="man/figures/README-/CPA-io-dark.svg"><img src="reference/figures/README-/CPA-io.svg" style="display: block; margin: auto;"></source></picture></p>
<p>Including random effects:</p>
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">chickweights_re_spec</span> <span class="op"><-</span> <span class="fu"><a href="reference/make_jlmer_spec.html">make_jlmer_spec</a></span><span class="op">(</span></span>
<span> formula <span class="op">=</span> <span class="va">weight</span> <span class="op">~</span> <span class="fl">1</span> <span class="op">+</span> <span class="va">Diet</span> <span class="op">+</span> <span class="op">(</span><span class="fl">1</span> <span class="op">|</span> <span class="va">Chick</span><span class="op">)</span>,</span>
<span> data <span class="op">=</span> <span class="va">chickweights</span>,</span>
<span> subject <span class="op">=</span> <span class="st">"Chick"</span>, time <span class="op">=</span> <span class="st">"Time"</span></span>
<span><span class="op">)</span></span>
<span><span class="fu"><a href="reference/julia_rng.html">set_rng_state</a></span><span class="op">(</span><span class="fl">123L</span><span class="op">)</span></span>
<span><span class="fu"><a href="reference/clusterpermute.html">clusterpermute</a></span><span class="op">(</span></span>
<span> <span class="va">chickweights_re_spec</span>,</span>
<span> threshold <span class="op">=</span> <span class="fl">2.5</span>,</span>
<span> nsim <span class="op">=</span> <span class="fl">100</span></span>
<span><span class="op">)</span><span class="op">$</span><span class="va">empirical_clusters</span></span></code></pre></div>
<p><picture><source media="(prefers-color-scheme: dark)" srcset="man/figures/README-/reCPA-io-dark.svg"><img src="reference/figures/README-/reCPA-io.svg" style="display: block; margin: auto;"></source></picture></p>
</div>
<div class="section level3">
<h3 id="piecemeal-approach-to-cpa">Piecemeal approach to CPA<a class="anchor" aria-label="anchor" href="#piecemeal-approach-to-cpa"></a>
</h3>
<p>Computing time-wise statistics of the observed data:</p>
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">empirical_statistics</span> <span class="op"><-</span> <span class="fu"><a href="reference/compute_timewise_statistics.html">compute_timewise_statistics</a></span><span class="op">(</span><span class="va">chickweights_spec</span><span class="op">)</span></span>
<span><span class="fu"><a href="https://rdrr.io/r/graphics/matplot.html" class="external-link">matplot</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/t.html" class="external-link">t</a></span><span class="op">(</span><span class="va">empirical_statistics</span><span class="op">)</span>, type <span class="op">=</span> <span class="st">"b"</span>, pch <span class="op">=</span> <span class="fl">1</span>, lwd <span class="op">=</span> <span class="fl">3</span>, ylab <span class="op">=</span> <span class="st">"t-statistic"</span><span class="op">)</span></span>
<span><span class="fu"><a href="https://rdrr.io/r/graphics/abline.html" class="external-link">abline</a></span><span class="op">(</span>h <span class="op">=</span> <span class="fl">2.5</span>, lty <span class="op">=</span> <span class="fl">3</span><span class="op">)</span></span></code></pre></div>
<p><img src="reference/figures/README-empirical_statistics-1.png" width="75%" style="display: block; margin: auto;"></p>
<p>Identifying empirical clusters:</p>
<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">empirical_clusters</span> <span class="op"><-</span> <span class="fu"><a href="reference/extract_empirical_clusters.html">extract_empirical_clusters</a></span><span class="op">(</span><span class="va">empirical_statistics</span>, threshold <span class="op">=</span> <span class="fl">2.5</span><span class="op">)</span></span>
<span><span class="va">empirical_clusters</span></span></code></pre></div>
<p><picture><source media="(prefers-color-scheme: dark)" srcset="man/figures/README-/empirical_clusters-dark.svg"><img src="reference/figures/README-/empirical_clusters.svg" style="display: block; margin: auto;"></source></picture></p>
<p>Simulating the null distribution:</p>
<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="reference/julia_rng.html">set_rng_state</a></span><span class="op">(</span><span class="fl">123L</span><span class="op">)</span></span>
<span><span class="va">null_statistics</span> <span class="op"><-</span> <span class="fu"><a href="reference/permute_timewise_statistics.html">permute_timewise_statistics</a></span><span class="op">(</span><span class="va">chickweights_spec</span>, nsim <span class="op">=</span> <span class="fl">100</span><span class="op">)</span></span>
<span><span class="va">null_cluster_dists</span> <span class="op"><-</span> <span class="fu"><a href="reference/extract_null_cluster_dists.html">extract_null_cluster_dists</a></span><span class="op">(</span><span class="va">null_statistics</span>, threshold <span class="op">=</span> <span class="fl">2.5</span><span class="op">)</span></span>
<span><span class="va">null_cluster_dists</span></span></code></pre></div>
<p><picture><source media="(prefers-color-scheme: dark)" srcset="man/figures/README-/null_statistics-dark.svg"><img src="reference/figures/README-/null_statistics.svg" style="display: block; margin: auto;"></source></picture></p>
<p>Significance testing the cluster-mass statistic:</p>
<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="reference/calculate_clusters_pvalues.html">calculate_clusters_pvalues</a></span><span class="op">(</span><span class="va">empirical_clusters</span>, <span class="va">null_cluster_dists</span>, add1 <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></code></pre></div>
<p><picture><source media="(prefers-color-scheme: dark)" srcset="man/figures/README-/calculate_clusters_pvalues-dark.svg"><img src="reference/figures/README-/calculate_clusters_pvalues.svg" style="display: block; margin: auto;"></source></picture></p>
<p>Iterating over a range of threshold values:</p>
<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="reference/walk_threshold_steps.html">walk_threshold_steps</a></span><span class="op">(</span><span class="va">empirical_statistics</span>, <span class="va">null_statistics</span>, steps <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">2</span>, <span class="fl">2.5</span>, <span class="fl">3</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
<p><picture><source media="(prefers-color-scheme: dark)" srcset="man/figures/README-/walk_threshold_steps-dark.svg"><img src="reference/figures/README-/walk_threshold_steps.svg" style="display: block; margin: auto;"></source></picture></p>
</div>
</div>
<div class="section level2">
<h2 id="acknowledgments">Acknowledgments<a class="anchor" aria-label="anchor" href="#acknowledgments"></a>
</h2>
<ul>
<li><p>The paper <a href="https://doi.org/10.1016/j.jneumeth.2007.03.024" class="external-link">Maris & Oostenveld (2007)</a> which originally proposed the cluster-based permutation analysis.</p></li>
<li><p>The <a href="https://github.com/stefan-m-lenz/JuliaConnectoR" class="external-link">JuliaConnectoR</a> package for powering the R interface to Julia.</p></li>
<li><p>The Julia packages <a href="https://github.com/JuliaStats/GLM.jl" class="external-link">GLM.jl</a> and <a href="https://github.com/JuliaStats/MixedModels.jl" class="external-link">MixedModels.jl</a> for fast implementations of (mixed effects) regression models.</p></li>
<li><p>Existing implementations of CPA in R (<a href="https://jaromilfrossard.github.io/permuco/" class="external-link">permuco</a>, <a href="https://cran.r-project.org/package=permutes" class="external-link">permutes</a>, etc.) whose designs inspired the CPA interface in jlmerclusterperm.</p></li>
</ul>
</div>
<div class="section level2">
<h2 id="citations">Citations<a class="anchor" aria-label="anchor" href="#citations"></a>
</h2>
<p>If you use jlmerclusterperm for cluster-based permutation test with mixed-effects models in your research, please cite one (or more) of the following as you see fit.</p>
<p>To cite jlmerclusterperm:</p>
<ul>
<li>Choe, J. (2023). jlmerclusterperm: Cluster-Based Permutation Analysis for Densely Sampled Time Data. R package version 1.1.2. <a href="https://cran.r-project.org/package=jlmerclusterperm" class="external-link uri">https://cran.r-project.org/package=jlmerclusterperm</a>.</li>
</ul>
<p>To cite the cluster-based permutation test:</p>
<ul>
<li>Maris, E., & Oostenveld, R. (2007). Nonparametric statistical testing of EEG- and MEG-data. <em>Journal of Neuroscience Methods, 164</em>, 177–190. doi: 10.1016/j.jneumeth.2007.03.024.</li>
</ul>
<p>To cite the Julia programming language:</p>
<ul>
<li>Bezanson, J., Edelman, A., Karpinski, S., & Shah, V. B. (2017). Julia: A Fresh Approach to Numerical Computing. <em>SIAM Review, 59</em>(1), 65–98. doi: 10.1137/141000671.</li>
</ul>
<p>To cite the GLM.jl and MixedModels.jl Julia libraries, consult their Zenodo pages:</p>
<ul>
<li>GLM: <a href="https://doi.org/10.5281/zenodo.3376013" class="external-link uri">https://doi.org/10.5281/zenodo.3376013</a>
</li>
<li>MixedModels: <a href="https://zenodo.org/badge/latestdoi/9106942" class="external-link uri">https://zenodo.org/badge/latestdoi/9106942</a>
</li>
</ul>
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<a href="https://yjunechoe.github.io" class="external-link">June Choe</a> <br><small class="roles"> Author, maintainer, copyright holder </small> <a href="https://orcid.org/0000-0002-0701-921X" target="orcid.widget" aria-label="ORCID" class="external-link"><span class="fab fa-orcid orcid" aria-hidden="true"></span></a> </li>
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