Hello Experts: I run into a difficulty to explain which independent variable is more predictive when running a Proc Logistic. In my proc Logistic procedure, I modeled the dependent variable (Event = '1'), see code below: proc logistic data=data_test; model p_flag (event = '1') = var1 var2 var3 / selection=stepwise; run; Then I get this results for the stepwise selection: Summary of Stepwise Selection Step Effect DF Number In Score Chi-Square Wald Chi-Square Pr > ChiSq Variable Label Entered Removed 1 var3   1 1 2006.955   <.0001   2 var2   1 2 150.3232   <.0001   3 var1   1 3 43.6837   <.0001   and the likelihood: Analysis of Maximum Likelihood Estimates Parameter DF Estimate Standard Error Wald Chi-Square Pr > ChiSq Intercept 1 -4.1428 0.1142 1316.869 <.0001 var1 1 1.083 0.1556 48.4503 <.0001 var2 1 -0.1256 0.00706 316.7223 <.0001 var3 1 0.2754 0.00463 3541.0916 <.0001 And the odd ratios: Odds Ratio Estimates Effect Point Estimate 95% Wald  Confidence Limits var1 2.954 2.177 4.007 var2 0.882 0.87 0.894 var3 1.317 1.305 1.329   So my question is: Which one of the 3 variables is the most predictable for p_flag =1? In the likelihood test, which output field I need to look into: estimate vs. Wald Chi-square?   Thanks a lot! LHK ... View more