Ordinal Logistic Regression with likert scale outcomes

[nickgarza19]

Hey all, 
I haven't worked with ordinal logistic regression before so I am trying to clear something up. I am looking at various demographic independent variables that may or may not predict a likert scale outcome. (disagree, neutral, agree). I have these coded as disagree=1, neutral=2, and agree=3. Should I model these in my class statement? I am inclined to - but I have seen examples where its treated as a continuous outcome. Any tips are appreciated. 

Thanks, 

[StatDave]

The outcome (response) variable in PROC LOGISTIC is always considered categorical, not continuous. It is never necessary to put it in the CLASS statement.

[Reeza · Accepted solution]

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@nickgarza19 wrote:

Hey all, 
I haven't worked with ordinal logistic regression before so I am trying to clear something up. I am looking at various demographic independent variables that may or may not predict a likert scale outcome. (disagree, neutral, agree). I have these coded as disagree=1, neutral=2, and agree=3. Should I model these in my class statement? I am inclined to - but I have seen examples where its treated as a continuous outcome. Any tips are appreciated. 

Thanks, 

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Independent variables ordinal/categorical data should go in your class statement.

Your outcome does not go in the class statement.

[nickgarza19]

Thank you! Sorry its been ages since I've used this.