I’m wondering what standard practice is when using a proportional odds model for many ordinal response questions in a survey. Does it make sense for the cutpoint parameters (or intercepts) to be the same for all questions of a similar type?
For example, suppose we have two questions about how much a respondent likes ice cream and another for cheese on a 5-point scale. If I fit two separate models I can’t easily compare the effect parameters since the underlying cutpoints might be different. If I share the cut points then I can make this comparison. I would assume that the latent continuous random variable would be binned similarly given the similarity of the questions.
Is this typically done?