• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Survey methodology >Estimation of response propensities and indicators of representative response using population-level information
【24h】

Estimation of response propensities and indicators of representative response using population-level information

机译：使用人群水平的信息估算响应倾向和代表性响应指标

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In recent years, there has been a strong interest in indirect measures of nonresponse bias in surveys or other forms of data collection. This interest originates from gradually decreasing propensities to respond to surveys parallel to pressures on survey budgets. These developments led to a growing focus on the representativeness or balance of the responding sample units with respect to relevant auxiliary variables. One example of a measure is the representativeness indicator, or R-indicator. The R-indicator is based on the design-weighted sample variation of estimated response propensities. It pre-supposes linked auxiliary data. One of the criticisms of the indicator is that it cannot be used in settings where auxiliary information is available only at the population level. In this paper, we propose a new method for estimating response propensities that does not need auxiliary information for non-respondents to the survey and is based on population auxiliary information. These population-based response propensities can then be used to develop R-indicators that employ population contingency tables or population frequency counts. We discuss the statistical properties of the indicators, and evaluate their performance using an evaluation study based on real census data and an application from the Dutch Health Survey.
机译：近年来，人们对调查或其他形式的数据收集中无响应偏差的间接测量方法产生了浓厚的兴趣。这种兴趣源自与调查预算压力平行的，逐渐降低的对调查做出回应的倾向。这些发展导致越来越多地关注响应样本单元相对于相关辅助变量的代表性或平衡性。度量的一个示例是代表性指标或R指标。 R指标基于估计响应倾向的设计加权样本变化。它以链接的辅助数据为前提。对该指标的批评之一是，它不能用于仅在人口一级可获得辅助信息的环境中。在本文中，我们提出了一种估计响应倾向的新方法，该方法不需要非受访者的辅助信息，而是基于人口辅助信息的。这些基于人口的响应倾向然后可以用于开发采用人口意外表或人口频率计数的R指标。我们讨论了指标的统计属性，并使用基于真实普查数据的评估研究和荷兰健康调查的应用程序来评估其性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号