Association between change scores of 2 ordinal variables Given that much has been written against the change-from-baseline analysis, what would be a principled way to quantify the correlation/association between change scores of 2 ordinal variables? I still see papers performing Spearman correlation analyses on the change scores but I have understood that an ordinal variable minus its baseline value is no longer ordinal (https://discourse.datamethods.org/t/analyzing-change-from-baseline-in-longitudinal-models/1768)
Thank you in advance for any guidance or assistance anyone may have.

You are right that if you are taking the difference of two ordinal values, that you are implicitly treating them as interval values.

*

*One option is to simply accept that you are treating your data as interval in nature and take the difference of the values in the analysis.


*If you want to treat the values as truly ordinal, when you take the difference between two values you can have a result of "greater", "equal", or "less".  These would also be ordinal values and could be analyzed accordingly.


*Technically, it may be possible to take the difference between two ordinal values, and end up with more than the three results described in 2).  For example, you could know that the difference between "agree" and "neutral" is greater than the difference between "strongly agree" and "agree", and then code the results accordingly.  But the circumstances where this makes sense are probably few.
