调查对象驱动抽样估计器对测量误差的鲁棒性研究。

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2022-04-01 DOI:10.1093/jssam/smab056

Ian E Fellows

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引用次数: 2

摘要

被调查者驱动抽样(RDS)是在难以接触到的人群中进行调查的一种流行方法，这些人群需要强有力的假设才能做出有效的统计推断。在本文中，我们研究了RDS调查准确测量网络度的假设，并发现典型研究可能存在显着的测量误差。我们证明了大多数RDS估计量在不完善的测量模型下保持一致，几乎没有额外的偏差，尽管估计量的方差确实增加了。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

On The Robustness Of Respondent-Driven Sampling Estimators To Measurement Error.

查看原文本刊更多论文

On The Robustness Of Respondent-Driven Sampling Estimators To Measurement Error.

Respondent-driven sampling (RDS) is a popular method of conducting surveys in hard to reach populations where strong assumptions are required in order to make valid statistical inferences. In this paper we investigate the assumption that network degrees are measured accurately by the RDS survey and find that there is likely significant measurement error present in typical studies. We prove that most RDS estimators remain consistent under an imperfect measurement model with little to no added bias, though the variance of the estimators does increase.

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来源期刊

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.