Example 79.3 Custom Scoring Coefficients

This example uses a specially created custom scoring data set and produces Output 79.3.1 and Output 79.3.2. The first scoring coefficient creates a variable that is AgeWeight; the second scoring coefficient evaluates the variable RunPulseRstPulse; 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 79.1) are not standardized before scoring.

The following statements produce Output 79.3.1 and Output 79.3.2:

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;

Output 79.3.1 Custom Scoring Data Set and Scored Fitness Data: PROC PRINT
Constructed Scoring Example
Scoring Coefficients

Obs _type_ _name_ Age Weight RunTime RunPulse RestPulse
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

Output 79.3.2 Custom Scored Fitness Data: PROC PRINT
Constructed Scoring Example
Scored Data

Obs Age Weight Oxygen RunTime RestPulse RunPulse 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