Non-Hierarchical Multilevel Models
Non-Hierarchical Multilevel Models
复制标题
非分层多级模型
DOI：
--
复制
发表时间：
2008
期刊：
影响因子：
--
通讯作者：
W. Browne
中科院分区：
文献类型：
--
作者：
J. Rasbash;W. Browne
到目前为止，在本书所讨论的模型中，我们都假设数据所来源的总体结构是分层的。这种假设有时是不合理的。在本章中，主要考虑两种类型的非层次模型。第一，交叉分类模型。交叉分类的概念对大多数读者来说可能是相当熟悉的。其次，我们考虑多个成员资格模型，其中较低级别的单位受到一个以上的较高级别的单位从同一分类。例如，有些学生可能就读不止一所学校。我们还考虑包含层次结构，交叉和多重成员关系的混合物的情况。
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.