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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.

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    $\begingroup$ You have ordered categories; if you take account of the ordering, you may find the results more interpretable. $\endgroup$
    – Glen_b
    Commented Nov 9, 2013 at 1:42
  • $\begingroup$ Thank you Glen. Does this sound like the appropriate test to use? $\endgroup$
    – user32544
    Commented Nov 9, 2013 at 1:46
  • $\begingroup$ 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. $\endgroup$
    – Glen_b
    Commented Nov 9, 2013 at 1:53
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    $\begingroup$ Adressing the question of categorical treatment of age and scores: Did you find out how to let your software treat them as numerical? $\endgroup$
    – Michael M
    Commented Nov 9, 2013 at 11:34
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    $\begingroup$ 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. $\endgroup$
    – Peter Flom
    Commented Nov 9, 2013 at 11:50

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First, if your DV is ordinal (that is, has an order, e.g. "small", "medium", "large") then a better starting point is probably ordinal logistic regression.

Second, the way SPSS is treating age and the test scores as categorical has nothing to do with nominal logistic regression. You somehow told SPSS that these variables are categorical. You need to tell it that they are numeric, or continuous, or whatever. I don't know SPSS so I don't know how to do this.

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