Design and analysis of more complex factorial experiments.

This chapter describes the design and analysis of randomized block experiments and more systematic designs such as split-plot, nested (or hierarchical), Latin square and repeated-measures designs developed to handle more complex experimental situations. Some examples are shown, including the application of analysis of variance (ANOVA) to a randomized complete block experiment using the data of a field trial on yield of 4 potato cultivars and to a multiple-factor randomized complete block design experiment using the data of a field trial on the effect of a fertilizer spray on the yield in 4 potato cultivars. A split-plot designed experiment is also shown using the yield of 3 different cultivars of glasshouse-grown strawberries in response to 3 day-length extension treatments.