Randomizing Designs

In many situations, proper randomization is crucial for the validity of any conclusions to be drawn from an experiment. Randomization is used both to neutralize the effect of any unknown systematic biases that might be involved in the design and to provide a basis for the assumptions underlying the analysis.

You can use PROC PLAN to randomize an already existing design: one produced by a previous call to PROC PLAN, perhaps, or a more specialized design taken from a standard reference such as Cochran and Cox (1957). The method is to specify the appropriate block structure in the FACTORS statement and then to specify the data set where the design is stored with the DATA= option in the OUTPUT statement. For an illustration of this method, see the section Randomly Assigning Subjects to Treatments).

Two sorts of randomization are provided for, corresponding to the RANDOM factor selection and association types in the FACTORS and OUTPUT statements, respectively. Designs in which factors are completely nested (for example, block designs) should be randomized by specifying that the selection type of each factor is RANDOM in the FACTORS statement, which is the default (see Example 67.3). On the other hand, if the factors are crossed (for example, row-and-column designs), they should be randomized by one random reassignment of their values for the whole design. To do this, specify that the association type of each factor is RANDOM in the OUTPUT statement (see Example 67.4).