Bivariate binomial spatial modeling of Loa loa prevalence in tropical Africa
Bivariate binomial spatial modeling of Loa loa prevalence in tropical Africa
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DOI：
10.1198/016214507000001409
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发表时间：
2008-03-01
影响因子：
3.7
通讯作者：
Rowlingson, Barry
中科院分区：
文献类型：
--
作者：
Crainiceanu, Ciprian M.;Diggle, Peter J.;Rowlingson, Barry
我们提出了一个国家的最先进的应用程序的平滑依赖双变量二项式空间数据Loa loa患病率映射在西非。该应用程序从调查仪器的非空间校准开始，继续进行空间模型的建立和评估，并以供现场工作人员在线更新流行地图使用的强大的经过测试的软件结束。从统计学的角度来看，我们解决了几个重要的方法问题：建立空间模型，足够复杂，捕捉数据的结构，但仍然计算上可用，减少计算负担，在处理非常大的协变量数据集，并设计方法比较空间预测方法为一个给定的服从政策阈值。
We present a state-of-the-art application of smoothing for dependent bivariate binomial spatial data to Loa loa prevalence mapping in West Africa. This application starts with the nonspatial calibration of survey instruments, continues with the spatial model building and assessment, and ends with robust, tested software intended for use by field workers for online prevalence map updating. From a statistical perspective, we address several important methodological issues: building spatial models that are sufficiently complex to capture the structure of the data but remain computationally usable, reducing the computational burden in the handling of very large covariate data sets, and devising methods for comparing spatial prediction methods for a given exceedance policy threshold.