title: R - plm regression with time in posix-format
body: <p>I have little experience with panel data in R, and am trying to run a simple panel regression with the plm-package. When converting my dataframe to a pdata.frame, however, my time index-variable is transformed to a factor variable. This means that if I want to regress a dependent variable as a function of time, the regression generates a long list of dummy-variables for time and calculates individual coefficients for each. I just want the average effect per time unit (ie. average monthly increase/decrease in points).</p>
  
  <p>Example dataframe:</p>
  
  <pre><code>ID    Date        Points
  1     1/11/2014   2
  1     1/12/2014   4
  1     1/1/2015    6
  1     1/2/2015    8
  2     1/11/2014   1
  2     1/12/2014   2
  2     1/1/2015    3
  2     1/2/2015    4
  </code></pre>
  
  <p>Say the example dataframe structure is ID = int, Date = POSIXct, Points = int.
  I then convert it to a pdata.frame with index ID and Date:</p>
  
  <pre><code>panel &lt;- pdata.frame(dataframe, c("ID", "Date"))
  </code></pre>
  
  <p>And run a plm fixed effects regression:</p>
  
  <pre><code>fixed &lt;- plm(Points ~ Date, data=panel, model="within")
  summary(fixed)
  </code></pre>
  
  <p>The resulting coefficients are then broken down by each month as dummies.
  I want to treat my time-variable as a continuous variable, so I get only one coefficient for Date. How can I do this? Is there a way to avoid formatting the time index-variable as a factor in panel dataframes?</p>