Comparison of Unit-Level Small Area Estimation Modeling Approaches for Survey Data Under Informative Sampling
Comparison of Unit-Level Small Area Estimation Modeling Approaches for Survey Data Under Informative Sampling
复制标题
信息抽样下调查数据单位级小区域估计建模方法比较
DOI：
10.1093/jssam/smad022
复制
发表时间：
2023
影响因子：
2.1
通讯作者：
Holan, Scott H
中科院分区：
文献类型：
--
作者：
Parker, Paul A;Janicki, Ryan;Holan, Scott H
单元级建模策略相对于最常用于小区域估计的区域级模型具有许多优势。例如，单位级模型自然聚合，允许以任何期望的分辨率进行估计，并且在许多情况下还提供更高的精度。我们比较了各种可用的方法在文献中有关的单位级建模小面积估计。具体来说，为了深入了解方法之间的差异，我们进行了模拟研究，比较了几种一般的方法。此外，用于模拟的方法进一步说明了通过应用到美国社区调查。
Unit-level modeling strategies offer many advantages relative to the area-level models that are most often used in the context of small area estimation. For example, unit-level models aggregate naturally, allowing for estimates at any desired resolution, and also offer greater precision in many cases. We compare a variety of the methods available in the literature related to unit-level modeling for small area estimation. Specifically, to provide insight into the differences between methods, we conduct a simulation study that compares several of the general approaches. In addition, the methods used for simulation are further illustrated through an application to the American Community Survey.