Bivariate binomial spatial modeling of Loa loa prevalence in tropical Africa

• 成果类型: Article
• 署名作者: Crainiceanu, Ciprian M.; Diggle, Peter J.; Rowlingson, Barry
• 署名单位: Johns Hopkins University; Lancaster University; Lancaster University
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1198/016214507000001409
• 发表日期: 2008
• 页码: 21-37
• 关键词: likelihood ratio tests; intensity

摘要

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.