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 68.3 and Figure 68.4:
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 68.3 shows that the 12 levels of the unit
factor have been randomly reordered and then lists the new ordering.
Figure 68.3: 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 68.4).
Figure 68.4: 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;