This example uses a specially created custom scoring data set and produces Output 64.3.1.Thefirst scoring coefficient creates a variable that is Age - Weight ;the second scoring coefficient evaluates the variable RunPulse - RstPulse ; and the third scoring coefficient totals all six variables . Since the scoring coefficients data set (data set A ) does not contain any observations with _TYPE_ ='MEAN' or _TYPE_ ='STD', the data in the Fitness data set (see Example 64.1) are not standardized before scoring.
CONSTRUCTED SCORING EXAMPLE Scoring Coefficients Run Run Rest Obs _type_ _name_ Age Weight Time Pulse Pulse 1 SCORE AGE_WGT 1 1 0 0 0 2 SCORE RUN_RST 0 0 0 1 1 3 SCORE TOTAL 1 1 1 1 1
data A; input _type_ $ _name_ $ Age Weight RunTime RunPulse RestPulse; datalines; SCORE AGE_WGT 1 -1 0 0 0 SCORE RUN_RST 0 0 0 1 -1 SCORE TOTAL 1 1 1 1 1 ; proc print data=A; title 'CONSTRUCTED SCORING EXAMPLE'; title2 'Scoring Coefficients'; run; proc score data=Fitness score=A out=B; var Age Weight RunTime RunPulse RestPulse; run; proc print data=B; title2 'Scored Data'; run;
CONSTRUCTED SCORING EXAMPLE Scored Data Run Rest Run Obs Age Weight Oxygen Time Pulse Pulse AGE_WGT RUN_RST TOTAL 1 44 89.47 44.609 11.37 62 178 45.47 116 384.84 2 40 75.07 45.313 10.07 62 185 35.07 123 372.14 3 44 85.84 54.297 8.65 45 156 41.84 111 339.49 4 42 68.15 59.571 8.17 40 166 26.15 126 324.32 5 38 89.02 49.874 9.22 55 178 51.02 123 369.24 6 47 77.45 44.811 11.63 58 176 30.45 118 370.08 7 40 75.98 45.681 11.95 70 176 35.98 106 373.93 8 43 81.19 49.091 10.85 64 162 38.19 98 361.04 9 44 81.42 39.442 13.08 63 174 37.42 111 375.50 10 38 81.87 60.055 8.63 48 170 43.87 122 346.50 11 44 73.03 50.541 10.13 45 168 29.03 123 340.16 12 45 87.66 37.388 14.03 56 186 42.66 130 388.69