I’m working with data from a medical score system that creates a score for a patient by adding up scores from 11 Likert-scale questions (I’m not a fan of this, but it’s a scale commonly used in the field and it’s the data I have). We are looking at differences in score between two groups. My first instinct was to use a proportional odds model. Another approach which is perhaps more faithful to the true data generating process would involve separate ordinal regressions for each item and then obtaining a posterior distribution for the summated score in both groups. This all said, I have a feeling linear regression might recover approximately the same effect in about 2 minutes.
How are summated scores typically handled?