Suppose I have insurance dataset with 2 categorical predictive variables: Gender (F/M) and Credit (A/B/C/D/E) I also have exposure variable Days that I will use as the weight in PROC HPGENSELECT. PROC HPGENSELECT data=InputData FCONV=1E-8 MAXITER=100 ITSUMMARY; CLASS Gender Credit; MODEL Loss = Gender Credit / dist= Tweedie (p=1.6) link=log; WEIGHT Days; ODS OUTPUT ParameterEstimates= PEs; RUN; PROC PRINT DATA = PEs; RUN; From 37108 - Setting reference levels for CLASS predictor variables (sas.com) I know that by default the levels are arranged in ascending alphanumeric order -> so M will become the base level for Gender, and E will become the base level for Credit. However, the prevalent classes using exposure variable Days are Gender = F and Credit = B. For example, I can use PROC SUMMARY to determine the prevalent class for each predictive variable: PROC SUMMARY data=InputData SUM PRINT MISSING; CLASS Gender; VAR Days; RUN; ... and then specify the preferred reference levels in the CLASS statement: PROC HPGENSELECT data=InputData FCONV=1E-8 MAXITER=100 ITSUMMARY; CLASS Gender(ref = "F") Credit(ref = "B"); MODEL Loss = Gender Credit / dist= Tweedie (p=1.6) link=log; WEIGHT Days; ODS OUTPUT ParameterEstimates= PEs; RUN; PROC PRINT DATA = PEs; RUN; If I have 10 more categorical predictive variables, is there an elegant way to avoid PROC SUMMARY, pass exposure variable Days to PROC HPGENSELECT, and request PROC HPGENSELECT for each categorical predictive variable use the level with the highest exposure as the base? Thanks for the insights! ... View more