ABSTRACT
A factorial design, the topic of this chapter, involves comparing responses for the response variable across the combinations of the levels of two or more grouping variables. In the context of an experiment, the grouping variables are called treatment variables. The classic factorial analysis of variance or ANOVA compares the means across the groups. As with the previous chapter, accomplish the analysis with the lessR function ANOVA(). More advanced designs need to rely directly on the R ANOVA function, aov(). One example of a more complex design is the randomized block factorial, which presents two or more dependent or matched samples. The other more complex design discussed is the split-plot factorial, which combines independent and dependent groups, one of each grouping variable discussed in this chapter. Analysis of unbalanced designs is also discussed.
