用ORRT模型估计分层连续抽样中无响应和测量误差下的均值

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
M. Choudhary, S. P. Kour, Sunil Kumar, C. Bouza, Agustín Santiago
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引用次数: 0

摘要

在抽样调查的情况下,收集敏感变量的信息是困难的,这可能导致无响应和测量误差。因此,估计可能会有偏差,变化可能会增加。为了克服这一困难,我们提出了在同时存在非响应和测量误差的情况下,利用辅助信息对敏感变量进行估计的估计器。研究了所提估计量的性质,并将结果与一般的完全响应估计量进行了比较。通过一个人工种群和两个实际应用的模拟研究,验证了理论结果。根据所建议的估计器的结果,已向调查统计人员提出了适合其实际应用的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using ORRT Models for Mean Estimation under Nonresponse and Measurement Errors in Stratified Successive Sampling
In the context of a sample survey, the collection of information on a sensitive variable is difficult, which may cause nonresponse and measurement errors. Due to this, the estimates can be biased and the variation may increase. To overcome this difficulty, we propose an estimator for the estimation of a sensitive variable by using auxiliary information in the presence of nonresponse and measurement errors simultaneously. The properties of the proposed estimators have been studied, and the results have been compared with those of the usual complete response estimator. Theoretical results have been verified through a simulation study using an artificial population and two real-life applications. With the outcomes of the proposed estimator, a suitable recommendation has been made to the survey statisticians for their real-life application.
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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