title: Residual variance for glmer model missing
body: <p>I am trying to calculate the <a href="https://en.wikipedia.org/wiki/Intraclass_correlation" rel="nofollow noreferrer">intraclass correlation</a> for a random intercept model fit with <code>glmer()</code> from the <code>lme4</code> package in <code>R</code>. </p>
  
  <p>Here is how the model looks:</p>
  
  <pre><code>model1 &lt;- lme4::glmer(funded ~ 
                            tweeted +
                            `Project Resource Type` + 
                            `Project Subject Category` +
                            `School Poverty Level` +
                        (1 | `School State`),
                        family = "binomial",
                        data = df)
  </code></pre>
  
  <p>Here is the output (fixed effects omitted):</p>
  
  <pre><code>Generalized linear mixed model fit by maximum likelihood (Laplace Approximation) ['glmerMod']
   Family: binomial  ( logit )
  Formula: funded ~ tweeted + `Project Resource Type` + `Project Subject Category` +  
      `School Poverty Level` + (1 | `School State`)
     Data: df
  
        AIC       BIC    logLik  deviance  df.resid 
   599914.4  600091.2 -299941.2  599882.4    465409 
  
  Scaled residuals: 
      Min      1Q  Median      3Q     Max 
  -2.2563 -1.2068  0.6538  0.7744  1.3985 
  
  Random effects:
   Groups       Name        Variance Std.Dev.
   School State (Intercept) 0.04272  0.2067  
  Number of obs: 465425, groups:  School State, 51
  </code></pre>
  
  <p>Beneath <code>Random effects:</code>, I expected there to be individual (in this case, an individual project from <a href="https://data.donorschoose.org/" rel="nofollow noreferrer">Donors Choose</a>) <code>Residual</code> <code>Variance</code> and <code>Std.Dev.</code> estimates, as well as the group (<code>School State</code>) <code>Variance</code> and <code>Std.Dev.</code> estimates, but there is not.</p>
  
  <p>Can these estimates be extracted from the output? Is there a reason it is not included? I recognize this may be a statistics-focused question relevant to Cross Validated, but I think because it is related to the output it is appropriate here.</p>