ABSTRACT
This chapter is concerned with the two-factor hierarchical model and the two-factor randomized block model, although these models can be generalized to designs with more than two factors. In general, randomized block designs have more power that completely randomized designs of equal size. The chapter describes the distinguishing characteristics of the two-factor randomized block analysis of variance (ANOVA) model for one observation per cell, the layout of the data, the linear model, assumptions and their violation, the ANOVA summary table and expected mean squares, multiple comparison procedures, and methods of block formation. The characteristics of the two-factor randomized block ANOVA model are quite similar to those of the regular two-factor ANOVA model, as well as sharing a few characteristics with the one-factor repeated measures ANOVA design. The chapter provides a preview into conducting hierarchical and randomized block ANOVA.
