The Use of Plackett and Burman Designs to Construct Split-Plot Designs

When some factors are hard to change and others are relatively easier, split-plot experiments are often an economic alternative to fully randomized designs. Split-plot experiments, with their structure of subplot arrays imbedded within whole-plot arrays, have a tendency to become large, particularly in screening situations when many factors are considered. To alleviate this problem, we explore, for the case of two-level designs, various ways to use orthogonal arrays of the Plackett-Burman type to reduce the number of individual tests. General construction principles are outlined, and the resulting alias structure is derived and discussed.