联合分位数疾病定位及其在疟疾和G6PD缺乏症中的应用
Joint Quantile Disease Mapping with Application to Malaria and G6PD Deficiency
摘要：
与均值回归方法相比，基于分位数回归方法的统计分析更全面、灵活，对离群值的敏感性更低。当对不同疾病之间的联系感兴趣时，关节疾病映射对于测量它们之间的方向相关性是有用的。大多数研究通过多重相关均值回归来研究这种联系。在本文中，我们提出了一个联合分位数回归框架，多个疾病，不同的分位数水平可以考虑。我们的动机是疟疾的存在和基因缺陷G6PD之间的理论联系，其中医学科学家已经发现了高水平的G6PD和低于预期水平的疟疾之间的可能联系，最初指向G6PD的发生抑制疟疾的发生。这种联系不能用均值回归来研究，因此需要在疾病映射框架中进行灵活的关节分位数回归。我们的联合分位数疾病映射模型可以用于随机样条的协变量的线性和非线性效应，因为我们将其定义为潜在高斯模型。我们使用嵌入在R软件包INLA中的INLA框架对该模型进行贝叶斯推断。最后，我们通过分析21个非洲国家的疟疾和G6PD缺乏症的发病率，使用不同水平的链接分位数来说明模型的适用性。
英文摘要：
Statistical analysis based on quantile regression methods is more comprehensive, flexible, and less sensitive to outliers when compared to mean regression methods. When the link between different diseases are of interest, joint disease mapping is useful for measuring directional correlation between them. Most studies study this link through multiple correlated mean regressions. In this paper we propose a joint quantile regression framework for multiple diseases where different quantile levels can be considered. We are motivated by the theorized link between the presence of Malaria and the gene deficiency G6PD, where medical scientist have anecdotally discovered a possible link between high levels of G6PD and lower than expected levels of Malaria initially pointing towards the occurrence of G6PD inhibiting the occurrence of Malaria. This link cannot be investigated with mean regressions and thus the need for flexible joint quantile regression in a disease mapping framework. Our joint quantile disease mapping model can be used for linear and non-linear effects of covariates by stochastic splines, since we define it as a latent Gaussian model. We perform Bayesian inference of this model using the INLA framework embedded in the R software package INLA. Finally, we illustrate the applicability of model by analyzing the malaria and G6PD deficiency incidences in 21 African countries using linked quantiles of different levels.
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