The values after the intercept level show me the change in relation to the intercept level, right?
Lets assume I have a covariate with 3 levels and I want to find out if there are differences between the groups. Can I just use the values of change and e.g. count how often level 2 shows values above/below zero and how often level 3 shows values above/below zero and compare them to each other? Or do I need to calculate the final values first (as described in the original post)?
Also I am wondering if this works, as e.g both level 2 and level 3 could potentially be greater/lower than the reference level, but still are different to each other. Ho do I capture that? May I compare level 2 and level 3 directly (after the utilities are calculates)?
So, if attribute level A in Covariate level 3 shows in 9500 rows, that the values are higher than attribute level A in Covariate level 2, means that level 3 is significantly different from level 2 and we are 95% confident that the level 3 has higher values than level 2. Is that right?
Thanks a lot!