I need to study which variables influence the change in a score after a treatment.
The problem is that the score (from 0 to 18) is actually the sum of six 4-levels (0 to 3) ordinal variables which represent the severity of a group of symptoms.
Which regression can help me model this outcome? Given the non-continuous nature of such dependent variable, an ordinal regression should be appropriate. But since we have 19 possible levels for the outcome maybe it's not the best choice (it's more a feeling, I would be glad if someone could formally explain me why). So maybe OLS linear regression is ok in this setting, or even better quasi-poisson, since the value can only be positive.
By the way, I know that summing up ordinal scores doesn't make really sense, but I need the have just one model, not one for each fo the six symptoms variables. If you have alternative designs to suggest for this kind of problem please do suggest it.