论文标题
具有不完整地理信息的健康和人口指标的估计
Estimation of Health and Demographic Indicators with Incomplete Geographic Information
论文作者
论文摘要
在低收入国家和中等收入国家中，家庭调查是一系列健康和人口指标的宝贵信息来源。越来越多的估计需要靶向干预措施并评估目标的进度。在大多数情况下，使用分层群集采样，簇对应于枚举区域。报告的地理信息各不相同。保存机密性的一个常见程序是，在已知算法下，群集的真实质心放置了一个抖动的位置。尤其是用于旧调查的另一种情况是报告集群中的地理区域。在本文中，我们描述了一个空间层次模型，其中我们在集群位置中解释了不准确性。我们开发的计算算法是快速的，并且避免了纯MCMC方法的大量计算。我们通过模拟模型的好处来说明，而不是天真的替代方案。
In low and middle income countries, household surveys are a valuable source of information for a range of health and demographic indicators. Increasingly, subnational estimates are required for targeting interventions and evaluating progress towards targets. In the majority of cases, stratified cluster sampling is used, with clusters corresponding to enumeration areas. The reported geographical information varies. A common procedure, to preserve confidentiality, is to give a jittered location with the true centroid of the cluster is displaced under a known algorithm. An alternative situation, which was used for older surveys in particular, is to report the geographical region within the cluster lies. In this paper, we describe a spatial hierarchical model in which we account for inaccuracies in the cluster locations. The computational algorithm we develop is fast and avoids the heavy computation of a pure MCMC approach. We illustrate by simulation the benefits of the model, over naive alternatives.
