Hello,
I was wondering whether anyone can explain to me why the function "mlogit" does not want to converge anymore when you change the base-outcome.
Usually, mlogit takes the largest category as the baseline - however, when I choose (a more logical) category as the base, it fails to run the model (becomes not concave after a couple of iterations).
I was wondering whether anyone can explain to me why the function "mlogit" does not want to converge anymore when you change the base-outcome.
Usually, mlogit takes the largest category as the baseline - however, when I choose (a more logical) category as the base, it fails to run the model (becomes not concave after a couple of iterations).
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