One-Way Classification

Abstract

In this chapter, we consider the random effect model involving only a single factor or variable in an experimental study involving a comparison of a set of treatments, where each of the treatments can be randomly assigned to experimental units. Such a layout is commonly known as the one-way classification or the completely randomized design. The one-way classification is the simplest and most useful model in statistics. In a one-way random effects model, treatments, groups, or levels of a factor are regarded to be a random sample from a large population. It is the simplest nontrivial and widely used variance component model. Moreover, the statistical concepts and tools developed to handle a one-way random model can be adapted to provide solutions to more complex models. Models involving two or more factors will be considered in succeeding chapters.