title: probit with clustered standard error - equivalent for Stata command
body: <p>I have the following <code>probit</code> command in Stata and look for the equivalent code in R:</p>
  
  <pre><code>probit mediation viol ethniccomp  lncrisisdur  lncapratio  lnten_mean durable_avg neighbors totaldem_nbrhd geostr medprev jointdem if newcrisis==1, cluster(crisno)
  </code></pre>
  
  <p>I am able to replicate the estimation results for the coefficients, however, not the corrected standard errors (which are clustered)</p>
  
  <pre><code>probit.3.1_1 &lt;- glm(mediation ~           viol+ethniccomp+lncrisisdur+lncapratio+lnten_mean+durable_avg+neighbors+
                      totaldem_nbrhd+geostr+medprev+jointdem,
                      data=as.data.frame(basedata[basedata$newcrisis==1,]), family=binomial (link=probit)) 
  </code></pre>
  
  <p>I am basically looking for the equivalent in R for the Stata option <code>cluster(crisno)</code>.</p>
  
  <p>I have seen this <a href="https://stackoverflow.com/questions/16498849/logistic-regression-with-robust-clustered-standard-errors-in-r">reply</a>, but as far as I can tell the proposed solution only refers to logit, not probit.</p>