        -1.15     0.00167</span>
<span class="co">#&gt; 10    10   -1.22    -1.45  1         -1.04   -0.439         -0.712   -0.643  </span>
<span class="co">#&gt; # … with 4,049 more rows, and 2 more variables: .chol.mar.resid &lt;dbl&gt;,</span>
<span class="co">#&gt; #   .mar.fitted &lt;dbl&gt;</span></code></pre></div>
<p>Utilizing the tibble output of <code><a href="../reference/hlm_resid.default.html">hlm_resid()</a></code>, we can easily plot the standardized LS residuals against explanatory variab