EDGAR can generate one common type of split-plot design, in which the experiment is arranged in blocks, each of which has one main plot of each treatment of the first factor, while each main plot has one sub-plot of each treatment of the second factor. Main plot treatments are randomised within blocks and sub-plot treatments are randomised within main plots. For instance, this is a design for an experiment in which four varieties of a plant (A-D) are infected with three isolates of a fungus (P-R); the experiment is in two blocks:
For example, you might run an experiment to find out the efficacy of a new drug. According to the Merck Manual, one factor that can affect how a patient responds to a drug is age . Therefore, you run the risk that your results might be affected by age as a confounding variable . A Solution is to set up randomized block design so that different age groups are spread across equally sized blocks. The table below shows a randomized block design for a hypothetical experiment that tests a new drug on 1,000 people:
This randomized block design contains equal blocks of 200 people from each age group, where they are assigned randomly to either the placebo or the real drug. Therefore, age is removed as a potential source of variability.