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My dependent variable is categorical (with 3 levels) and my predictor variables are a mix of continuous (age in months, test 1 score, test 2 score, test 3 score) and categorical (gender). I believe I should run a multinomial regression, but when I do the results are really uninterpretable because each age is basically treated as a category (and the same for the test scores).

Does anyone know a different test that would be appropriate to use in my case? I would really appreciate any help.

Andre Silva
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user32544
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    You have ordered categories; if you take account of the ordering, you may find the results more interpretable. – Glen_b Nov 09 '13 at 01:42
  • Thank you Glen. Does this sound like the appropriate test to use? – user32544 Nov 09 '13 at 01:46
  • I'm not sure what you refer to by 'this'. I meant things like proportional odds models, adjacent category logit, cumulative models, and so on. – Glen_b Nov 09 '13 at 01:53
  • See the answers [here](http://stats.stackexchange.com/questions/56923/attempting-to-investigate-a-relationship-between-one-variable-and-another-that-h/56942#56942) and [here](http://stats.stackexchange.com/a/60908/805) for some of the possibilities – Glen_b Nov 09 '13 at 01:58
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    Adressing the question of categorical treatment of age and scores: Did you find out how to let your software treat them as numerical? – Michael M Nov 09 '13 at 11:34
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    Sounds to me like you are treating age, a continuous independent variable (unless the range of months is small) as categorical. I don't know of any methods for ordinal IVs. – Peter Flom Nov 09 '13 at 11:50
  • You should tell us what is your categorical dependent/response variable, without knowing that we are blind. And you could model age using splines! – kjetil b halvorsen Mar 17 '18 at 13:26

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