Estimation of Sensitive Proportion by Randomized Response Data in Successive Sampling

Author:

Yu Bo12ORCID,Jin Zongda3ORCID,Tian Jiayong4,Gao Ge1ORCID

Affiliation:

1. School of Public Health, Medical College, Soochow University, Suzhou 215123, China

2. School of Mathematical Sciences, Dezhou University, Dezhou 253023, China

3. Department of Public Health, Zhejiang Medical College, Hangzhou 310053, China

4. Critical Care Medicine, People’s Hospital of Linshu County, Linyi, Shandong 276700, China

Abstract

This paper considers the problem of estimation for binomial proportions of sensitive or stigmatizing attributes in the population of interest. Randomized response techniques are suggested for protecting the privacy of respondents and reducing the response bias while eliciting information on sensitive attributes. In many sensitive question surveys, the same population is often sampled repeatedly on each occasion. In this paper, we apply successive sampling scheme to improve the estimation of the sensitive proportion on current occasion.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Applied Mathematics,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation,General Medicine

Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Use of Free Software to Estimate Sensitive Behaviours from Complex Surveys;Trends in Mathematical, Information and Data Sciences;2022-06-28

2. An efficient new scrambled response model for estimating sensitive population mean in successive sampling;Communications in Statistics - Simulation and Computation;2021-10-10

3. Partial optional randomized response technique with calibration weighting to adjust non-response in successive sampling;Communications for Statistical Applications and Methods;2021-09-30

4. Surveying Sensitive Topics with Indirect Questioning;Statistical Methodologies;2020-02-26

5. Application of item sum technique for estimating quantitative sensitive mean on successive moves using auxiliary information;Communications in Statistics - Simulation and Computation;2020-02-12

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