How to assess information content / mutual information between 2 sets of variables ?

Question

[Khader Shameer]

Am testing data from a clinical device; data was extracted using two complementary methods

• Method 1: Existing method, 17 variables
• Method 2: New method, 13 variables

I need to quantitatively and visually explain that the information content / mutual information of both methods are the same.

I have correlation data but I am looking for an intuitive way to explain that irrespective of differences in number of variables between the data extraction methods and direction of correlation the information captured by methods are comparable.

Please let me know your thoughts, thanks in advance!

Cross-posted from here

Answer 1

[Ahill]

If you showed by linear regression that each of the 17 existing method variables was approximately equal to some linear combination of the 13 new variables, that would be fairly convincing that you've captured the same information in both methods.