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+    <div class="page-header">
+    <h1>Calculate mean degradation parameters for an mmkin row object</h1>
+    <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/mean_degparms.R'><code>R/mean_degparms.R</code></a></small>
+    <div class="hidden name"><code>mean_degparms.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Calculate mean degradation parameters for an mmkin row object</p>
+    </div>
+
+    <pre class="usage"><span class='fu'>mean_degparms</span><span class='op'>(</span><span class='va'>object</span>, random <span class='op'>=</span> <span class='cn'>FALSE</span>, test_log_parms <span class='op'>=</span> <span class='cn'>FALSE</span>, conf.level <span class='op'>=</span> <span class='fl'>0.6</span><span class='op'>)</span></pre>
+
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>object</th>
+      <td><p>An mmkin row object containing several fits of the same model to different datasets</p></td>
+    </tr>
+    <tr>
+      <th>random</th>
+      <td><p>Should a list with fixed and random effects be returned?</p></td>
+    </tr>
+    <tr>
+      <th>test_log_parms</th>
+      <td><p>If TRUE, log parameters are only considered in
+the mean calculations if their untransformed counterparts (most likely
+rate constants) pass the t-test for significant difference from zero.</p></td>
+    </tr>
+    <tr>
+      <th>conf.level</th>
+      <td><p>Possibility to adjust the required confidence level
+for parameter that are tested if requested by 'test_log_parms'.</p></td>
+    </tr>
+    </table>
+
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>If random is FALSE (default), a named vector containing mean values
+of the fitted degradation model parameters. If random is TRUE, a list with
+fixed and random effects, in the format required by the start argument of
+nlme for the case of a single grouping variable ds.</p>
+
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