A general modelling framework for multivariate disease mapping
A general modelling framework for multivariate disease mapping
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DOI：
10.1093/biomet/ast023
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发表时间：
2013-09-01
期刊：
影响因子：
2.7
通讯作者：
Martinez-Beneito, Miguel A.
中科院分区：
文献类型：
--
作者：
Martinez-Beneito, Miguel A.
本文讨论了多变量疾病映射。我们提出了一个新的框架，它包含了大多数已经提出的模型。我们的框架从一个简单的恒等式开始，将协方差矩阵的克罗内克积重新表述为简单矩阵积。这个公式在计算上很方便，它的概括再现了疾病制图文献中的大多数建议。同一性的使用导致灵活、通用和计算方便的建模框架，从而可以以有限的努力将空间依赖结构和疾病之间的不同关系结合起来。此外，由于所提出的建模框架涵盖了文献中大多数基于高斯马尔可夫随机场的多变量疾病映射模型，因此它允许在共同背景下对所有这些模型进行比较，从而帮助我们更好地理解它们。
This paper deals with multivariate disease mapping. We propose a novel framework that encompasses most of the models already proposed. Our framework starts with a simple identity, reformulating Kronecker products of covariance matrices as simple matrix products. This formula is computationally convenient, and its generalizations reproduce most of the proposals in the disease mapping literature. Use of the identity leads to a flexible, general and computationally convenient modelling framework, making it possible to combine spatial dependence structures and different relationships between diseases with limited effort. Moreover, as the proposed modelling framework covers most of the Gaussian Markov random field-based multivariate disease mapping models in the literature, it allows comparison of all these models in a common context, thus helping us to understand them better.