Mitigating lack of trust in quantitative randomized response technique models-Reference-Cited by-同舟云学术

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Mitigating lack of trust in quantitative randomized response technique models

Published:2022-06-03 Issue: Volume: Page:1-9
ISSN:0361-0918
Container-title:Communications in Statistics - Simulation and Computation
language:en
Short-container-title:Communications in Statistics - Simulation and Computation

Author:

Gupta Sat¹,Zhang Joia²,Khalil Sadia³,Sapra Pujita¹

Affiliation:

1. Department of Mathematics and Statistics, University of North Carolina at Greensboro, Greensboro, North Carolina, USA

2. Department of Statistics, University of Washington, Seattle, Washington, USA

3. Department of Statistics, Lahore College for Women University, Lahore, Pakistan

Funder

NSF

Publisher

Informa UK Limited

Subject

Modeling and Simulation,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/03610918.2022.2082477

Reference17 articles.

1. A class of estimators for quantitative sensitive data

2. Estimation of sensitivity level of personal interview survey questions

3. A unified measure of respondent privacy and model efficiency in quantitative RRT models

4. Mean and sensitivity estimation in optional randomized response models

5. The bogus pipeline: A new paradigm for measuring affect and attitude.

Cited by 12 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. A new unified measure for evaluation of randomized response techniques;Heliyon;2024-08

2. A novel randomized scrambling technique for mean estimation of a finite population;Heliyon;2024-06

3. A Ratio Estimator for the of Mean of a Sensitive Variable in the Presence of Lack of Trust in RRT and Measurement Errors;2024-05-21

4. A versatile optional randomized response technique for use with sensitive surveys;VFAST Transactions on Mathematics;2024-04-27

5. A Mixture Quantitative Randomized Response Model That Improves Trust in RRT Methodology;Axioms;2023-12-22

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