Dear Statalisters,

I'm using Stata 15.1.

I have an ordinal outcome that may assume 5 distinct values. Among my predictors, I have some variables representing percentages summing up to 100. For example, I have 5 age groups that are mutually exclusive and include all possible age values. I know I can use the "autofit" option of the gologit2 command to test which parameters fulfill the proportional odds assumption at a given significance value. Nevertheless, I'm afraid that, with linearly depend variables as age-group rates, results would change basing on the reference category I select. Is there a way to avoid such arbitrariness?

First of all, is there a way for Stata to perform it automatically (with gologit2, oglm or any other command)?

Otherwise, I thought about replicating the "gologit2, autofit" behaviour manually, by comparing separate models (i.e., a reference model M* vs a model only differing from M* in the proportional odds assumptions for a single variable). Do I well understand that gologit2 is basically using a stepwise procedure, i.e. starting with a no-constraint model and then adding one-by-one the constraints with the highest (i.e., closer to 1) p-value, until tests for proportional odds are significant for all parameters?