Hi,
I see what you are saying. Your original question was within the scope of EM. Since you did not indicate EM in your question, I thought you were asking about something else CALIS.
Lift in the Association Node is based on the fact the unit of analysis there is transaction. Lift concept is to see how much 'stimulus' the presence of A provides to boost transactions of B. If you sell diapers alone, you sell 50 one night. Now you put beer by the diaper in your store, sales of diapers go up to 100. So the beer is lifting the diaper by 100%? See the lift of beer?
The exercise at the Path Analysis node essentially is to count paths. One could observe along one specific path which path is most likely to follow next, and after that which path is to follow the second, like a tree branching out. Based on this weight of descriptive evidence, one can infer a little bit which are the most likely path combinations. But this exercise essentially is just count inference. In predictive modeling or analytics, wherever a lift concept is engaged, there is always a control/treatment situation. The 'tree branch' nature of the path analysis simply does not study that relation pattern. Therefore no lift is defined.
In typical score models, you break down model universe by scores into, say 10 groups. Then you compare random performance against model treated performance by the groups. The lift defined there is genuine because each group being assessed lift is identical (and fully controlled); it is a real per-group measurement. In the Association node, the element of marginal lift is borrowed/stolen from the genuine lift concept to measure the impact from presence of A on purchase of B. But there is no way the group that purchases B is equal to the group of purchasing A and B. The group underlying the 'lift' is by definition not the same, therefore by definition of the association study, not controlled. So they have to put the word 'pseudo' in front of it.. Hope this helps? Thanks. Jason Xin
