Hi, Yes, Distribution AND Tree should both work. You can try and tell the difference. Tree method is more informativeness friendly while distribution method remains univariate essentially. Please pay attention to the distribution inside the non-missing subgroups +the % size of the non-missing. For argument sake, if you only have 1% non-missing, I am hard-pressed to do it. Converting to 'flags': this idea is always intriguing, in the sense that the resulting indicators by definition are associated with the sourcing element. In the linear regression context, classically we 'stay away' from categorical variable, almost by instinct. But facilities in EM or SAS STAT are equally robust supporting categorical variables, in variable selection and estimation, by way of, say, the CLASS statement. The chance is if you derive indicator, you can only use one of them, if it is useful after all. You could use decision tree in EM to run a test. Make sure all the performance reading is off validation data set. Best Regards Jason Xin ... View more