Abstract This chapter discusses the basic principles underlying experimental design: replication, randomization, and blocking. It differentiates experimental from survey designs, and discusses five of the most frequently used experimental designs in the life sciences: factorial, randomized blocks, repeated measures, crossover, split-plot, and nested designs. For each experimental design, it highlights the underlying assumptions, the application, and the structure of the data set. For each design, we show how to include the structure or restrictions in randomization imposed by experimental and survey designs as random (group-level) effects in mixed/hierarchical models.
Stored only when both papers are in the corpus — 91 citations exist upstream.
Imported from OpenAlex (CC0) — nothing here is generated.