title: Covariance parameter estimates table in R
body: <p>I have created a random intercept and slope model (<code>lmer</code>) and need to inspect the covariances of the random effects to see which is significant.</p>
  
  <p>I've seen that SAS outputs provide a <em>'covariance parameter estimates'</em> table as part of the model summary - see section <em>'Output 56.2.6 Repeated Measures Analysis'</em> of <a href="https://support.sas.com/documentation/cdl/en/statug/63033/HTML/default/viewer.htm#statug_mixed_sect031.htm#statug.mixed.mixx2c" rel="noreferrer">PROC MIXED</a></p>
  
  <p>Is there a way of doing this (and obtaining p values for each covariance) in R?</p>