title: Regression model without predictors using plm in R?
body: <p>I have an unbalance panel data table with variables <code>ID</code>, <code>year</code>, and <code>outcome</code>. The data for each <code>ID</code> spans from 2005-2020, although each <code>ID</code> won't have all 15 years of data. Here's a sample:</p>
  <pre><code>ID, year, outcome
  1, 2005, 70
  1, 2006, 73
  1, 2007, 70
  1, 2008, 68
  2, 2005, 65
  2, 2006, 71
  2, 2007, 68
  2, 2008, 64
  2, 2009, 63
  3, 2011, 78
  3, 2012, 81
  4, 2008, 75
  </code></pre>
  <p>I want to run a <code>plm</code> regression model <strong>without predictors</strong> (i.e. a regression model on the intercept).</p>
  <p>I tried running the following but get the error message &quot;empty model&quot;:</p>
  <pre><code>feModel &lt;- plm(damMean ~ 1, data = finalDT, model = &quot;within&quot;, index = c(&quot;sireID&quot;, &quot;year&quot;))
  
  # Error in plm.fit(data, model, effect, random.method, random.models, random.dfcor,  : 
    empty model
  </code></pre>
  <p>Is this possible to do using the <code>plm</code> package in R?</p>