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or emmeans::ref_grid() applied to a Bayesian model."><meta property="og:image" content="https://mjskay.github.io/tidybayes/logo.svg"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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    <div class="page-header">
    <h1>Extract a tidy data frame of draws of posterior distributions of "estimated marginal means" (emmeans/lsmeans) from a Bayesian model fit.</h1>
    <small class="dont-index">Source: <a href="https://github.com/mjskay/tidybayes/blob/HEAD/R/gather_emmeans_draws.R" class="external-link"><code>R/gather_emmeans_draws.R</code></a></small>
    <div class="hidden name"><code>gather_emmeans_draws.Rd</code></div>
    </div>

    <div class="ref-description">
    <p>Extract draws from the result of a call to <code><a href="https://rvlenth.github.io/emmeans/reference/emmeans.html" class="external-link">emmeans::emmeans()</a></code> (formerly <code>lsmeans</code>)
or <code><a href="https://rvlenth.github.io/emmeans/reference/ref_grid.html" class="external-link">emmeans::ref_grid()</a></code> applied to a Bayesian model.</p>
    </div>

    <div id="ref-usage">
    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">gather_emmeans_draws</span><span class="op">(</span><span class="va">object</span>, value <span class="op">=</span> <span class="st">".value"</span>, <span class="va">...</span><span class="op">)</span></span>
<span></span>
<span><span class="co"># Default S3 method</span></span>
<span><span class="fu">gather_emmeans_draws</span><span class="op">(</span><span class="va">object</span>, value <span class="op">=</span> <span class="st">".value"</span>, <span class="va">...</span><span class="op">)</span></span>
<span></span>
<span><span class="co"># S3 method for class 'emm_list'</span></span>
<span><span class="fu">gather_emmeans_draws</span><span class="op">(</span><span class="va">object</span>, value <span class="op">=</span> <span class="st">".value"</span>, grid <span class="op">=</span> <span class="st">".grid"</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
    </div>

    <div id="arguments">
    <h2>Arguments</h2>


<dl><dt id="arg-object">object<a class="anchor" aria-label="anchor" href="#arg-object"></a></dt>
<dd><p>An <code>emmGrid</code> object such as returned by
<code><a href="https://rvlenth.github.io/emmeans/reference/ref_grid.html" class="external-link">emmeans::ref_grid()</a></code> or <code><a href="https://rvlenth.github.io/emmeans/reference/emmeans.html" class="external-link">emmeans::emmeans()</a></code>.</p></dd>


<dt id="arg-value">value<a class="anchor" aria-label="anchor" href="#arg-value"></a></dt>
<dd><p>The name of the output column to use to contain the values of draws. Defaults to <code>".value"</code>.</p></dd>


<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
<dd><p>Additional arguments passed to the underlying method for the type of object given.</p></dd>


<dt id="arg-grid">grid<a class="anchor" aria-label="anchor" href="#arg-grid"></a></dt>
<dd><p>If <code>object</code> is an <code><a href="https://rvlenth.github.io/emmeans/reference/emm_list-object.html" class="external-link">emmeans::emm_list()</a></code>, the name of the output column to use to contain the name of the
reference grid that a given row corresponds to. Defaults to <code>".grid"</code>.</p></dd>

</dl></div>
    <div id="value">
    <h2>Value</h2>
    <p>A tidy data frame of draws. The columns of the reference grid are returned as-is, with an
additional column called <code>.value</code> (by default) containing marginal draws. The resulting data
frame is grouped by the columns from the reference grid to make use of summary functions like
<code><a href="http://mjskay.github.io/ggdist/reference/point_interval.html" class="external-link">point_interval()</a></code> straightforward.</p>
<p>If <code>object</code> is an <code><a href="https://rvlenth.github.io/emmeans/reference/emm_list-object.html" class="external-link">emmeans::emm_list()</a></code>, which contains estimates from different reference grids,
an additional column with the default name of <code>".grid"</code> is added to indicate the reference grid for each row in the output.
The name of this column is controlled by the <code>grid</code> argument.</p>
    </div>
    <div id="details">
    <h2>Details</h2>
    <p><code><a href="https://rvlenth.github.io/emmeans/reference/emmeans.html" class="external-link">emmeans::emmeans()</a></code> provides a convenient syntax for generating draws from "estimated marginal means" from a model,
and can be applied to various Bayesian models, like <a href="https://mc-stan.org/rstanarm/reference/stanreg-objects.html" class="external-link">rstanarm::stanreg-objects</a> and
<code><a href="https://rdrr.io/pkg/MCMCglmm/man/MCMCglmm.html" class="external-link">MCMCglmm::MCMCglmm()</a></code>. Given a <code><a href="https://rvlenth.github.io/emmeans/reference/ref_grid.html" class="external-link">emmeans::ref_grid()</a></code> object as returned by functions like
<code><a href="https://rvlenth.github.io/emmeans/reference/ref_grid.html" class="external-link">emmeans::ref_grid()</a></code> or <code><a href="https://rvlenth.github.io/emmeans/reference/emmeans.html" class="external-link">emmeans::emmeans()</a></code> applied to a Bayesian model,
<code>gather_emmeans_draws</code> returns a tidy format data frame of draws from
the marginal posterior distributions generated by <code><a href="https://rvlenth.github.io/emmeans/reference/emmeans.html" class="external-link">emmeans::emmeans()</a></code>.</p>
    </div>
    <div id="see-also">
    <h2>See also</h2>
    <div class="dont-index"><p><code><a href="https://rvlenth.github.io/emmeans/reference/emmeans.html" class="external-link">emmeans::emmeans()</a></code></p></div>
    </div>
    <div id="author">
    <h2>Author</h2>
    <p>Matthew Kay</p>
    </div>

    <div id="ref-examples">
    <h2>Examples</h2>
    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># \dontrun{</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><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://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span></span>
<span class="r-in"><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://magrittr.tidyverse.org" class="external-link">magrittr</a></span><span class="op">)</span></span></span>
<span class="r-in"><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/paul-buerkner/brms" class="external-link">brms</a></span><span class="op">)</span></span></span>
<span class="r-in"><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://rvlenth.github.io/emmeans/" class="external-link">emmeans</a></span><span class="op">)</span></span></span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> Welcome to emmeans.</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> Caution: You lose important information if you filter this package's results.</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> See '? untidy'</span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># Here's an example dataset with a categorical predictor (`condition`) with several levels:</span></span></span>
<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/Random.html" class="external-link">set.seed</a></span><span class="op">(</span><span class="fl">5</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">n</span> <span class="op">=</span> <span class="fl">10</span></span></span>
<span class="r-in"><span><span class="va">n_condition</span> <span class="op">=</span> <span class="fl">5</span></span></span>
<span class="r-in"><span><span class="va">ABC</span> <span class="op">=</span> <span class="fu"><a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a></span><span class="op">(</span></span></span>
<span class="r-in"><span>  condition <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></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">"A"</span>,<span class="st">"B"</span>,<span class="st">"C"</span>,<span class="st">"D"</span>,<span class="st">"E"</span><span class="op">)</span>, <span class="va">n</span><span class="op">)</span>,</span></span>
<span class="r-in"><span>  response <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/Normal.html" class="external-link">rnorm</a></span><span class="op">(</span><span class="va">n</span> <span class="op">*</span> <span class="fl">5</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">0</span>,<span class="fl">1</span>,<span class="fl">2</span>,<span class="fl">1</span>,<span class="op">-</span><span class="fl">1</span><span class="op">)</span>, <span class="fl">0.5</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="va">m</span> <span class="op">=</span> <span class="fu"><a href="https://paul-buerkner.github.io/brms/reference/brm.html" class="external-link">brm</a></span><span class="op">(</span><span class="va">response</span> <span class="op">~</span> <span class="va">condition</span>, data <span class="op">=</span> <span class="va">ABC</span>,</span></span>
<span class="r-in"><span>  <span class="co"># 1 chain / few iterations just so example runs quickly</span></span></span>
<span class="r-in"><span>  <span class="co"># do not use in practice</span></span></span>
<span class="r-in"><span>  chains <span class="op">=</span> <span class="fl">1</span>, iter <span class="op">=</span> <span class="fl">500</span><span class="op">)</span></span></span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> Compiling Stan program...</span>
<span class="r-msg co"><span class="r-pr">#&gt;</span> Start sampling</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> SAMPLING FOR MODEL 'anon_model' NOW (CHAIN 1).</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: Gradient evaluation took 5.3e-05 seconds</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.53 seconds.</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: Adjust your expectations accordingly!</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: Iteration:   1 / 500 [  0%]  (Warmup)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: Iteration:  50 / 500 [ 10%]  (Warmup)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: Iteration: 100 / 500 [ 20%]  (Warmup)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: Iteration: 150 / 500 [ 30%]  (Warmup)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: Iteration: 200 / 500 [ 40%]  (Warmup)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: Iteration: 250 / 500 [ 50%]  (Warmup)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: Iteration: 251 / 500 [ 50%]  (Sampling)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: Iteration: 300 / 500 [ 60%]  (Sampling)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: Iteration: 350 / 500 [ 70%]  (Sampling)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: Iteration: 400 / 500 [ 80%]  (Sampling)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: Iteration: 450 / 500 [ 90%]  (Sampling)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: Iteration: 500 / 500 [100%]  (Sampling)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1:  Elapsed Time: 0.012 seconds (Warm-up)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1:                0.006 seconds (Sampling)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1:                0.018 seconds (Total)</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Chain 1: </span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># Once we've fit the model, we can use emmeans() (and functions</span></span></span>
<span class="r-in"><span><span class="co"># from that package) to get whatever marginal distributions we want.</span></span></span>
<span class="r-in"><span><span class="co"># For example, we can get marginal means by condition:</span></span></span>
<span class="r-in"><span><span class="va">m</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
<span class="r-in"><span>  <span class="fu"><a href="https://rvlenth.github.io/emmeans/reference/emmeans.html" class="external-link">emmeans</a></span><span class="op">(</span><span class="op">~</span> <span class="va">condition</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
<span class="r-in"><span>  <span class="fu">gather_emmeans_draws</span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
<span class="r-in"><span>  <span class="fu"><a href="http://mjskay.github.io/ggdist/reference/point_interval.html" class="external-link">median_qi</a></span><span class="op">(</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 5 × 7</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span>   condition .value .lower .upper .width .point .interval</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>      <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">1</span> A          0.191 -<span style="color: #BB0000;">0.128</span>  0.542   0.95 median qi       </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">2</span> B          1.02   0.685  1.35    0.95 median qi       </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">3</span> C          1.87   1.54   2.21    0.95 median qi       </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">4</span> D          1.03   0.683  1.37    0.95 median qi       </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">5</span> E         -<span style="color: #BB0000;">0.948</span> -<span style="color: #BB0000;">1.30</span>  -<span style="color: #BB0000;">0.584</span>   0.95 median qi       </span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># or we could get pairwise differences:</span></span></span>
<span class="r-in"><span><span class="va">m</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
<span class="r-in"><span>  <span class="fu"><a href="https://rvlenth.github.io/emmeans/reference/emmeans.html" class="external-link">emmeans</a></span><span class="op">(</span><span class="op">~</span> <span class="va">condition</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
<span class="r-in"><span>  <span class="fu"><a href="https://rvlenth.github.io/emmeans/reference/contrast.html" class="external-link">contrast</a></span><span class="op">(</span>method <span class="op">=</span> <span class="st">"pairwise"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
<span class="r-in"><span>  <span class="fu">gather_emmeans_draws</span><span class="op">(</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span></span>
<span class="r-in"><span>  <span class="fu"><a href="http://mjskay.github.io/ggdist/reference/point_interval.html" class="external-link">median_qi</a></span><span class="op">(</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 10 × 7</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    contrast    .value .lower .upper .width .point .interval</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>        <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> A - B    -<span style="color: #BB0000;">0.834</span>    -<span style="color: #BB0000;">1.27</span>  -<span style="color: #BB0000;">0.305</span>   0.95 median qi       </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> A - C    -<span style="color: #BB0000;">1.67</span>     -<span style="color: #BB0000;">2.15</span>  -<span style="color: #BB0000;">1.18</span>    0.95 median qi       </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> A - D    -<span style="color: #BB0000;">0.823</span>    -<span style="color: #BB0000;">1.29</span>  -<span style="color: #BB0000;">0.360</span>   0.95 median qi       </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> A - E     1.13      0.646  1.70    0.95 median qi       </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> B - C    -<span style="color: #BB0000;">0.862</span>    -<span style="color: #BB0000;">1.38</span>  -<span style="color: #BB0000;">0.368</span>   0.95 median qi       </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> B - D     0.000<span style="text-decoration: underline;">319</span> -<span style="color: #BB0000;">0.526</span>  0.510   0.95 median qi       </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> B - E     1.97      1.44   2.47    0.95 median qi       </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> C - D     0.865     0.349  1.31    0.95 median qi       </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> C - E     2.82      2.34   3.28    0.95 median qi       </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> D - E     1.98      1.50   2.42    0.95 median qi       </span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># see the documentation of emmeans() for more examples of types of</span></span></span>
<span class="r-in"><span><span class="co"># contrasts supported by that packge.</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># }</span></span></span>
</code></pre></div>
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