论文标题
有条件自回归模型的多个会员转换引起的结构
Structure induced by a multiple membership transformation on the Conditional Autoregressive model
论文作者
论文摘要
疾病映射的目的是建模在面积水平上汇总的数据。但是，在某些情况下，（例如，住宅历史，总从业者集水区域）当数据来自多种来源（不一定在相同的空间范围内）时，可以使用多个成员原理（MM）（MM）（MM）（petrof et an gramatate an an gramatate an and 2020 an an and 2020 an an and and 2020 an and 2020 an and careale corpe and care and carty scatial量表。有条件自回旋（CAR）的空间随机效应的加权平均值嵌入了空间信息，以获得空间 - 安装的结果，并估算两个框架（区域和成员资格）的相对风险。在本文中，我们调查了在参数化，适当性和可识别性方面，将多个成员原则应用于CAR的这些应用的理论基础。与区域数量相比，我们进行涉及不同数量的会员资格的模拟，并评估该会员对估计目标参数的影响。分析和仿真研究结果均表明在哪些感兴趣的条件参数是可识别的，因此我们可以向从业者提供可行的建议。最后，我们介绍了多个会员模型在伦敦南部的糖尿病患病率数据中应用的结果，以及对公共卫生注意事项的战略意义
The objective of disease mapping is to model data aggregated at the areal level. In some contexts, however, (e.g. residential histories, general practitioner catchment areas) when data is arising from a variety of sources, not necessarily at the same spatial scale, it is possible to specify spatial random effects, or covariate effects, at the areal level, by using a multiple membership principle (MM) (Petrof et al. 2020, Gramatica et al. 2021). A weighted average of conditional autoregressive (CAR) spatial random effects embeds spatial information for a spatially-misaligned outcome and estimate relative risk for both frameworks (areas and memberships). In this paper we investigate the theoretical underpinnings of these application of the multiple membership principle to the CAR prior, in particular with regard to parameterisation, properness and identifiability. We carry out simulations involving different numbers of memberships as compared to number of areas and assess impact of this on estimating parameters of interest. Both analytical and simulation study results show under which conditions parameters of interest are identifiable, so that we can offer actionable recommendations to practitioners. Finally, we present the results of an application of the multiple membership model to diabetes prevalence data in South London, together with strategic implications for public health considerations
