Non-hierarchical multilevel models

Abstract

In the models discussed in this book so far we have assumed that the structures of the populations from which the data have been drawn are hierarchical. This assumption is sometimes not justified. In this chapter two main types of non-hierarchical model are considered. Firstly, cross-classified models. The notion of cross-classification is probably reasonably familiar to most readers. Secondly, we consider multiple membership models, where lower level units are influenced by more than one higher-level unit from the same classification. For example, some pupils may attend more than one school. We also consider situations that contain a mixture of hierarchical, crossed and multiple membership relationships. © 2008 Springer Science+Business Media, LLC.