The PLAN Procedure

Overview: PLAN Procedure

The PLAN procedure constructs designs and randomizes plans for factorial experiments, especially nested and crossed experiments and randomized block designs. PROC PLAN can also be used for generating lists of permutations and combinations of numbers. The PLAN procedure can construct the following types of experimental designs:

  • full factorial designs, with and without randomization

  • certain balanced and partially balanced incomplete block designs

  • generalized cyclic incomplete block designs

  • Latin square designs

For other kinds of experimental designs, especially fractional factorial, response surface, and orthogonal array designs, see the FACTEX and OPTEX procedures and the ADX Interface in SAS/QC software.

PROC PLAN generates designs by first generating a selection of the levels for the first factor. Then, for the second factor, PROC PLAN generates a selection of its levels for each level of the first factor. In general, for a given factor, the PLAN procedure generates a selection of its levels for all combinations of levels for the factors that precede it.

The selection can be done in five different ways:

  • randomized selection, for which the levels are returned in a random order

  • ordered selection, for which the levels are returned in a standard order every time a selection is generated

  • cyclic selection, for which the levels returned are computed by cyclically permuting the levels of the previous selection

  • permuted selection, for which the levels are a permutation of the integers $1,\dots , n$

  • combination selection, for which the m levels are selected as a combination of the integers $1,\dots , n$ taken m at a time

The randomized selection method can be used to generate randomized plans. Also, by appropriate use of cyclic selection, any of the designs in the very wide class of generalized cyclic block designs (Jarrett and Hall 1978) can be generated.

There is no limit to the depth to which the different factors can be nested, and any number of randomized plans can be generated.

You can also declare a list of factors to be selected simultaneously with the lowest (that is, the most nested) factor. The levels of the factors in this list can be seen as constituting the treatment to be applied to the cells of the design. For this reason, factors in this list are called treatments. With this list, you can generate and randomize plans in one run of PROC PLAN.