Dear all, Here's the code. 1. proc logistic data=slide.sb_vm_training outmodel=slide.model; CLASS N2 N3 N4 N5 N6 N7 N10 N11 N12 N13 /param=ref; model dv = Prin1 Prin2 Prin3 factor1 factor2 factor3 factor4 factor5 factor6 factor7 factor8 /selection=stepwise ; run; 2. proc logistic data=slide.sb_vm_training outmodel=slide.model; CLASS N2 N3 N4 N5 N6 N7 N10 N11 N12 N13 /param=effect; model dv = Prin1 Prin2 Prin3 factor1 factor2 factor3 factor4 factor5 factor6 factor7 factor8 /selection=stepwise ; run; 3. proc logistic data=slide.sb_vm_training outmodel=slide.model; CLASS N2 N3 N4 N5 N6 N7 N10 N11 N12 N13 /param=ref; model dv = Prin1 Prin2 Prin3 factor1 factor2 factor3 factor4 factor5 factor6 factor7 factor8 /selection=stepwise ; unit Prin1=Prin1 =50000 Prin2 =50000 Prin3 =50000 run; I tried the 3 different coding as above, but all failed to get a N variable into the model Where variables with prefix "N" are ordinal variables like nationality,sex,most of them with the scope (0,9) Prin1-prin3 are variables extracted from principal analysis,the scope for this variable is between (-Million,+Million) factor1-factor8 are variables extracted from factor analysis,the scope for this variable is between (-2,+2) both of them are summary of continous variables in some way, dv is the dependent variable , with 1 shows the customer will leave, and 0 shows he will stay. The question is when using stepwise, only prin1 and some factor variables remains, not even one N variable remains. while judge from the real business, at least nationality is very useful to determine whether a customer will leave, WHY not even one N variable remains? what's wrong with my coding for Proc Logistic? Thanks in Advance. Dawn
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