title: Can MICE pool results of ordinal logistic regression run by the function polr()?
body: <p>I'm running the data set downloaded from UCLA </p>
  
  <pre><code>read.dta("https://stats.idre.ucla.edu/stat/data/ologit.dta")
  </code></pre>
  
  <p>and randomly assign some missing values in the independent variables: pared, public, and gpa. Then I use mice to generate imputed values and run the ordinal logistic regression for the 5 complete data set with imputed values.</p>
  
  <pre><code>DAT.imp=mice(DAT,print=FALSE)
  DAT.fit.mice.plr = with(DAT.imp, polr(apply ~ pared + public + gpa))
  summary(DAT.fit.mice.plr)
  </code></pre>
  
  <p>But the error message shows as follows:</p>
  
  <pre><code>Error in as.data.frame.default(x) : 
   cannot coerce class ""polr"" to a data.frame
  </code></pre>
  
  <p>Is it a problem because the pool() function cannot run models not belong to lm?
  Should I run the model by polr() separately for the 5 imputed data sets and manually pool them?
  Thanks in advance for any response.</p>