敏感变量均值的双抽样回归指数估计

IF 1.4 3区社会学 Q3 DEMOGRAPHY

Mathematical Population Studies Pub Date : 2019-03-11 DOI:10.1080/08898480.2019.1565273

Iram Saleem, A. Sanaullah, M. Hanif

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引用次数: 17

摘要

摘要一种灵活的加扰响应模型，使用随机化装置对定量敏感数据进行随机化，用于评估受访者隐私的保护。双采样回归指数估计器用于在加扰响应下使用非敏感辅助变量的均值来估计敏感变量的均值。表达了该指数型估计器的期望偏差、期望均方误差和最小均方误差。仿真和经验结果表明，在加扰响应模型下，所提出的估计量比比率和指数估计量具有更低的均方误差和更低的偏差。

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Double-sampling regression-cum-exponential estimator of the mean of a sensitive variable

ABSTRACT A flexible scrambled response model using a randomization device for quantitative sensitive data is used to evaluate the protection of respondents’ privacy. A double-sampling regression-cum-exponential estimator is used to estimate the mean of a sensitive variable using the mean of a nonsensitive auxiliary variable under scrambled response. The expected bias, the expected mean square error, and the minimum mean square error of this exponential-type estimator are expressed. Simulations and empirical results show that the proposed estimator under scrambled response model has a lower mean square error and a lower bias than the ratio and the exponential estimators.

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来源期刊

Mathematical Population Studies 数学-数学跨学科应用

CiteScore

3.20

自引率

11.10%

发文量

审稿时长

>12 weeks

期刊介绍： Mathematical Population Studies publishes carefully selected research papers in the mathematical and statistical study of populations. The journal is strongly interdisciplinary and invites contributions by mathematicians, demographers, (bio)statisticians, sociologists, economists, biologists, epidemiologists, actuaries, geographers, and others who are interested in the mathematical formulation of population-related questions. The scope covers both theoretical and empirical work. Manuscripts should be sent to Manuscript central for review. The editor-in-chief has final say on the suitability for publication.