title: Python statsmodels: Regression summary, how to get p-value for reference dummy variable?
body: <p>I am running MNLogit (multinomial logistic regression) as follows: </p>
  
  <pre><code>from statsmodels.formula.api import MNLogit
  model=MNLogit.from_formula("y ~ x", df).fit()
  model.summary()
  </code></pre>
  
  <p>The variable y is categorical and seems to be automatically dummy encoded by the MNLogit function. The summary output gives a row for each category of y except for the reference category.</p>
  
  <p>1) How can I get the identity of the reference category? (It is tedious to figure this out manually due to the many categories for y)</p>
  
  <p>2) As there is no z or P>|z| (p-value) given for the reference category, how can I assess significance for the reference category?</p>
  
  <p>3) How can I change which category is treated as the reference category?</p>