Impact of survey quality on composite indicators
Impact of survey quality on composite indicators
复制标题
调查质量对综合指标的影响
DOI：
10.1108/sampj-10-2013-0045
复制
发表时间：
2014
期刊：
影响因子：
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通讯作者：
J. Seger
中科院分区：
文献类型：
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作者：
R. Münnich;J. Seger
目的-本研究的目的是说明在使用综合指标时充分考虑质量措施的重要性。政策支持往往依赖于高质量的指标。相关指标的基础数据往往主要来自抽样调查。显然，指标的可靠性在很大程度上取决于抽样设计和其他质量方面。设计/方法/方式-从众所周知的工作指标的敏感性分析，本研究集成了抽样过程作为一个额外的变异源。在接近现实的模拟环境中，使用不同抽样设计的相关和重要的调查评估方法。作为一个例子，这项研究使用了与收入和生活条件统计有关的数据。这项研究是基于一个基于设计的仿真框架。结果-在一般情况下，归一化方法是占主导地位的CI的总方差的来源。在我们的研究中，我们
Purpose – The purpose of this study is to show the importance of adequately considering quality measures within the use of composite indicators (CIs). Policy support often relies on high quality indicators. Often, the underlying data of relevant indicators are coming mainly from sample surveys. Obviously, the reliability of the indicators then heavily relies on the sampling design and other quality aspects. Design/methodology/approach – Starting from the well-known work on sensitivity analysis of indicators, this study integrates the sampling process as an additional source of variability. The methodology is evaluated in a close-to-reality simulation environment using relevant and important surveys with different sampling designs. As an example, this study uses data related to the statistics of income and living conditions (SILC). The study is based on a design-based simulation framework. Findings – In general, the normalisation method is dominating as source of the total variance of CI. In our study, we ...