title: Why exact matching with MatchIt R package finds matched pairs that have 2 different levels of categorical variable?
body: <p>I'm actually working on tuna tag-recapture data. I want to balance my sampling between two groups of individuals, the ones that where tagged in the reference area (Treated group) and the ones that where tagged outside this area (Control group). To do this, I used the <code>MatchIt</code> package.</p>
  
  <p>I have 3 covariates: length (by 5 cm bins), month of tagging (January to December) and structure on which the tuna was tagged.</p>
  
  <p>So there is the model: <code>treatment ~ length + month + structure</code></p>
  
  <p>This last variable, is a categorical variable with 5 levels coded as A to E. The level A is almost only represented in the Treated group (6000 individuals with structure = A, vs on 300 individuals with structure = A in control group). </p>
  
  <p>I first used the nearest neighbour method, but the improvement in balance was not satisfying. So I ran exact and Coarsened Exact Matching methods.</p>
  
  <p>I though that Exact methods should match pairs with the same values for each covariates. But in the output matched data, there are still more than 3000 individuals with structure = A in the treated group.</p>
  
  <p>Do you guys have one explanation ? I red a lot but I didn't find answers.</p>
  
  <p>Thanks</p>