Uplift Model in EMiner- Finding significance/lift of the variables

SGhosh — Mon, 25 Sep 2017 16:10:22 GMT

Hello,

Is there a way to know the significant for each variable? I see in the output window that most influencing variables has maximum of wald chi square. However, I am trying to figure out how these variables are influencing. For example I did this manual calculation and here is the outcome:

member_age_grp	reg_rate_Control	reg_rate_Test	Lift
18-24	4.3%	4.9%	13.5%
25-34	5.4%	5.9%	8.6%
35-44	4.5%	4.6%	1.6%
45-54	3.6%	3.6%	(0.0%)
55-64	2.5%	3.6%	41.7%

•Members who are 55-64 years old show significant lift in registration rates (41.7%) from receiving the letter. Members between 45-54 doesn't show any lift in terms of receiving letters and this could be because of low sample size

But how could I figure out this lift from SAS EMiner. Can something like this (anything that could show how a veriable is influencing the model or the lift) though the EM_ variables?

Thanks a lot again!

Soma

Re: Uplift Model in EMiner- Finding significance/lift of the variables

Ruiwen — Tue, 03 Oct 2017 02:24:57 GMT

If I understand correctly, what you need is to calculate the netlift by certain variable, like "age" in your example. We don't provide it in the node, but you can obtain the percentage by calling proc freq or using data step code.

The Net Weight of Evidence (NWOE) plot in the Results window shows the absolute NWOE at each level for categorical variables. You can see how the levels of a variable differentiate between the control group and treatment group in terms of WOE.

Hope this helps.

topic Uplift Model in EMiner- Finding significance/lift of the variables in SAS Data Science

Uplift Model in EMiner- Finding significance/lift of the variables

Re: Uplift Model in EMiner- Finding significance/lift of the variables