I'm analyzing survey results with many responses coming in the form of Likert scales. In this case, I actually have two Likert scale predictors (in the model as nominal variables) predicting my ordinal dependent variable. My two predictors each have five categories (levels on the scale). My dependent variable also has 5 levels.

My test is failing the proportional odds assumption so I've done two things to explore further. First I've run individual logistic regressions on each of the cutpoints in my dependent variable. These did not yield significant relationships for most IV-DV combinations (cells).

I also did the parallel lines test for each of category of my predictor variables (inputted as dummies) on my ordinal dependent variable. In most of these categories, the parallel lines test is failed (i.e. the proportional odds assumption is updheld). However, in a couple of these categories, I have no observations (nobody responded Very Poor or Poor on one of my predictor Likert scales). Thus I cannot get a parallel lines P-value for these categories.

I guess that these categories are what's causing my full model to fail the parallel lines test. My question is whether, since nobody responded Very Poor or Poor, I can report odds ratios from my full model without fear that these predictor categories will throw off the results.

Many thanks to whoever might take the time to answer this question. I would appreciate it tremendously. Have a nice day All!