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The PLAN Procedure

Specifying Factor Structures

By appropriately combining features of the PLAN procedure, you can construct an extensive set of designs. The basic tools are the factor-selections, which are used in the FACTORS and TREATMENTS statements. Table 50.1 summarizes how the procedure interprets various factor-selections (assuming that the ORDERED option is not specified in the PROC PLAN statement).

Table 50.1: Factor Selection Interpretation
Form of      
Request Interpretation Example Results
name=mproduce a random permutation of the integers 1,2, ... ,m.t=15lists a random ordering of the numbers 1,2, ... ,15.
name=m cycliccyclically permute the integers 1,2, ... ,m.t=5 cyclicselects the integers 1 to 5. On the next iteration, selects 2,3,4,5,1; then 3,4,5,1,2; and so on.
name=m of nchoose a random sample of m integers (without replacement) from the set of integers 1,2, ... ,n.t=5 of 15lists a random selection of 5 numbers from 1 to 15. First, the procedure selects 5 numbers and then arranges them in random order.
name=m of n orderedhas the same effect as name=m ordered.t=5 of 15 orderedlists the integers 1 to 5 in increasing order (same as t=5 ordered).
name=m of n cyclicpermute m of the n integers.t=5 of 30 cyclicselects the integers 1 to 5. On the next iteration, selects 2,3,4,5,6; then 3,4,5,6,7; and so on. The 30th iteration 30,1,2,3,4; the 31st iteration produces 1,2,3,4,5; and so on.
name=m permproduce a list of all permutations of m integers.t=5 permlists the integers 1,2,3,4,5 on the first iteration; on the second lists 1,2,3,5,4; and on the 119th iteration lists 5,4,3,1,2; and on the last (120th) lists 5,4,3,2,1.
name=m of n combchoose combinations of m integers from n integers.t=3 of 5 comblists all combinations of 5 choose 3 integers. The first iteration is 1,2,3; the second is 1,2,4; the third is 1,2,5; and so on until the last iteration 3,4,5.
name=m of n cyclic (initial-block)permute m of the n integers, starting with the values specified in the initial-block.t=4 of 30 cyclic (2 10 15 18)selects the integers 2,10,15,18. On the next iteration, selects 3,11,16,19; then 4,12,17,20; and so on. The thirteenth iteration is 14,22,27,30; the fourteenth iteration is 15,23,28,1; and so on.
name=m of n cyclic (initial-block) incrementpermute m of the n integers. Start with the values specified in the initial-block, then add the increment to each value.t=4 of 30 cyclic (2 10 15 18) 2selects the integers 2,10,15,18. On the next iteration, selects 4,12,17,20; then 6,14,19,22; and so on. The wrap occurs at the eighth iteration. The eighth iteration is 16,24,29,2; and so on.

In Table 50.1, in order for more than one iteration to appear in the plan, another name=j factor selection (with j>1) must precede the example factor selection. For example, the following statements produce six of the iterations described in the last entry of Table 50.1.

   proc plan;
      factors c=6 ordered t=4 of 30 cyclic (2 10 15 18) 2;
   run;

The following statements create a randomized complete block design and output the design to a data set.

   proc plan ordered;
      factors blocks=3 cell=5;
      treatments t=5 random;
      output out=rcdb;
   run;

Table 50.2 lists other kinds of experiment designs that can be constructed by PROC PLAN, along with section and page references for them in this chapter.

Table 50.2: Experimental Design Examples
Design Page Number
Completely randomized designthis page
Split-plot designthis page
Nested designthis page
Latin square designthis page
Generalized cyclic incomplete block designthis page

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