MCMC Sampling for a Multilevel Model With Nonindependent Residuals Within and Between Cluster Units
MCMC Sampling for a Multilevel Model With Nonindependent Residuals Within and Between Cluster Units
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DOI：
10.3102/1076998609359788
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发表时间：
2010-08
影响因子：
2.4
通讯作者：
W. Browne;H. Goldstein
中科院分区：
文献类型：
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作者：
W. Browne;H. Goldstein
在本文中，我们讨论了删除两水平随机效应模型中残差之间的独立性假设的影响。我们首先考虑去除2级残差之间的独立性，并假设聚类级别上所有残差的向量遵循一般的多元正态分布。我们演示了如何通过一个教育的例子，这个假设可以让我们适应更高层次的集群和学校竞争的影响。然后，我们考虑删除集群内的1级残差之间的独立性的假设。我们将展示如何扩展可以允许时间序列类型的模型。正常和二进制响应被认为是。
In this article, we discuss the effect of removing the independence assumptions between the residuals in two-level random effect models. We first consider removing the independence between the Level 2 residuals and instead assume that the vector of all residuals at the cluster level follows a general multivariate normal distribution. We demonstrate how this assumption can allow us to fit higher levels of clustering and school competition effects via an example from education. We then consider removing the assumption of independence between Level 1 residuals within clusters. We show how this extension can allow time series type models. Both normal and binary responses are considered.