(View the complete code for this example.)
You can use the PLAN procedure to design a completely randomized design. Suppose you have 12 experimental units, and you want to assign one of two treatments to each unit. Use a DATA step to store the unrandomized design in a SAS data set, and then call PROC PLAN to randomize it by specifying one factor with the default type of RANDOM, having 12 levels. The following statements produce Figure 3 and Figure 4:
title 'Completely Randomized Design';
/* The unrandomized design */
data Unrandomized;
do Unit=1 to 12;
if (Unit <= 6) then Treatment=1;
else Treatment=2;
output;
end;
run;
/* Randomize the design */
proc plan seed=27371;
factors Unit=12;
output data=Unrandomized out=Randomized;
run;
proc sort data=Randomized;
by Unit;
run;
proc print;
run;
Figure 3 shows that the 12 levels of the unit factor have been randomly reordered and then lists the new ordering.
Figure 3: A Completely Randomized Design for Two Treatments
| Completely Randomized Design |
| Factor | Select | Levels | Order |
|---|---|---|---|
| Unit | 12 | 12 | Random |
| Unit | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| 8 | 5 | 1 | 4 | 6 | 2 | 12 | 7 | 3 | 9 | 10 | 11 |
After the data set is sorted by the unit variable, the randomized design is displayed (Figure 4).
Figure 4: A Completely Randomized Design for Two Treatments
| Completely Randomized Design |
| Obs | Unit | Treatment |
|---|---|---|
| 1 | 1 | 1 |
| 2 | 2 | 1 |
| 3 | 3 | 2 |
| 4 | 4 | 1 |
| 5 | 5 | 1 |
| 6 | 6 | 1 |
| 7 | 7 | 2 |
| 8 | 8 | 1 |
| 9 | 9 | 2 |
| 10 | 10 | 2 |
| 11 | 11 | 2 |
| 12 | 12 | 2 |
You can also generate the plan by using a TREATMENTS statement instead of a DATA step. The following statements generate the same plan.
proc plan seed=27371;
factors Unit=12;
treatments Treatment=12 cyclic (1 1 1 1 1 1 2 2 2 2 2 2);
output out=Randomized;
run;