群体均值随机响应技术的无偏方差估计

IF 0.3 Q4 ECONOMICS
Ondřej Vozár
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引用次数: 0

摘要

Antoch、Mola和Vozár(2022)最近提出了一种新的定量变量群体平均值或总数的随机响应技术。本文的目的是解决这些过程的无偏方差估计的开放问题。在他们的提案中,与其他群体平均值或总值的随机响应技术不同,随机响应不是敏感变量的线性函数。然而,在这种情况下推导方差估计量的标准技术是基于这种假设的。这就是为什么访谈者还需要知道伪随机数的值(即个体随机化实验的结果)。受访者可能认为这种放松隐私保护的做法是负面的。通过对无替换的简单随机抽样的模拟研究,评估了不同形状分布(包括其覆盖范围)的近似双侧置信区间的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unbiased Variance Estimator of the Randomised Response Techniques for Population Mean
Antoch, Mola and Vozár (2022) proposed recently new randomized response technique for population mean or total of a quantitative variable. The aim of the paper is to solve the open problem to derive unbiased variance estimator of these procedures. In their proposal, unlike other randomized response techniques for population mean or total the randomized response is not a linear function of a sensitive variable. However, standard techniques to derive variance estimators in this setting are based on this assumption. That is why an interviewer needs also to know values pseudorandom numbers (i.e., results of individual randomization experiments). Respondents might perceive this relaxation of privacy protection negative. The performance of the approximate two-sided confidence intervals of distributions with different shape including their coverage is assessed by a simulation study for simple random sampling without replacement.
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来源期刊
CiteScore
0.60
自引率
0.00%
发文量
23
审稿时长
24 weeks
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