From start to finish: a framework for the production of small area official statistics

From start to finish: a framework for the production of small area official statistics
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自始至终:小区域官方统计数据制作框架

DOI:
10.1111/rssa.12364
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发表时间:
2018
期刊:
Journal of the Royal Statistical Society: Series A (Statistics in Society)
影响因子:
--
通讯作者:
Natalia Rojas
Natalia Rojas
中科院分区:
--
文献类型:
--
作者:
N. Tzavidis;Li‐Chun Zhang;Angela Luna;T. Schmid;Natalia Rojas

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小面积估计是官方统计和调查统计中的一个研究领域,对国家统计机构和有关组织具有很大的实际意义。尽管方法和软件发展迅速,但研究人员和用户将受益于小面积估算过程的实用指南。我们提出了一个小地区统计数据编制的总体框架,该框架遵循简约原则,基于三个定义广泛的阶段,即规格说明、分析和调整以及评价。重点是小地区统计数据的用户与统计人员之间的互动,根据现有数据确定目标地理和参数。无模型和依赖模型的方法被描述,重点是模型选择和测试,模型诊断和适应,如使用数据转换。不确定性度量以及使用模型和基于设计的模拟进行方法评估也是本文的核心。我们通过使用真实的数据估计非线性剥夺指标来说明所提出的框架的应用。线性统计,例如平均数,作为一般框架的特殊情况包括在内。
Small area estimation is a research area in official and survey statistics of great practical relevance for national statistical institutes and related organizations. Despite rapid developments in methodology and software, researchers and users would benefit from having practical guidelines for the process of small area estimation. We propose a general framework for the production of small area statistics that is governed by the principle of parsimony and is based on three broadly defined stages, namely specification, analysis and adaptation, and evaluation. Emphasis is given to the interaction between a user of small area statistics and the statistician in specifying the target geography and parameters in the light of the available data. Model‐free and model‐dependent methods are described with a focus on model selection and testing, model diagnostics and adaptations such as use of data transformations. Uncertainty measures and the use of model and design‐based simulations for method evaluation are also at the centre of the paper. We illustrate the application of the proposed framework by using real data for the estimation of non‐linear deprivation indicators. Linear statistics, e.g. averages, are included as special cases of the general framework.
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