Sometimes multi-factor experiments use multiple (different) experimental units for the various factors in the experiment. To visualize this, think of applying multiple treatments in a sequence. The levels of the first factor are applied to experimental units using some form of randomization. Following that, the levels of second Factor are applied to sub-units within the application of the first factor. In other words, the experimental unit used for the application of the first factor has been split, forming the experimental units for the application of the levels of the second treatment.
Split plot designs are extremely common, and typically result from logistical restrictions, practicality, or efficiency. Sometimes split plots are difficult to recognize, and it emphasizes the absolute necessity of determining what the experimental unit(s) are in setting up an ANOVA.
Split plots occur most commonly in two experimental designs: the CRD and RCBD. The ANOVA differs between these two, and we will carefully look at split plots in each setting.
Split plots can be extended to accommodate multiple splits. For example, it is not uncommon to see a split-split-plot experimental design being used. In this case, there are three experimental units involved and three stages of randomization of treatment levels.
- Recognizing multiple experimental units in an experimental design
- Understanding the structure of split-plot ANOVA
- Split plots administered in RCBD experiments
- Split plots administered in CRD experiments
- Extending the split-plot concept to analyze split-split plot designs