A mixture binary RRT model with a unified measure of privacy and efficiency-Reference-Cited by-同舟云学术

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A mixture binary RRT model with a unified measure of privacy and efficiency

Published:2021-04-24 Issue: Volume: Page:1-12
ISSN:0361-0918
Container-title:Communications in Statistics - Simulation and Computation
language:en
Short-container-title:Communications in Statistics - Simulation and Computation

Author:

Lovig Maxwell¹,Khalil Sadia²,Rahman Sumaita³,Sapra Pujita⁴,Gupta Sat⁴

Affiliation:

1. Mathematics, University of Louisiana at Lafayette, Lafayette, Louisiana, USA

2. Statistics, LCWU, Lahore, Pakistan

3. Computer Science, UNC Greensboro, Greensboro, North Carolina, USA

4. Mathematics and Statistics, UNC Greensboro, Greensboro, North Carolina, USA

Funder

NSF

Publisher

Informa UK Limited

Subject

Modelling and Simulation,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/03610918.2021.1914092

Reference17 articles.

1. A comparison of two randomized response survey methods with consideration for the level of respondent protection

2. The Unrelated Question Randomized Response Model: Theoretical Framework

3. Estimation of sensitivity level of personal interview survey questions

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

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

Cited by 9 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. Accounting for Measurement Error and Untruthfulness in Binary RRT Models;Mathematics;2024-03-16

3. Reproducibility of Statistical Tests Based on Randomised Response Data;Journal of Statistical Theory and Practice;2024-02-22

4. Binary Randomized Response Technique (RRT) models under measurement error;Communications in Statistics - Simulation and Computation;2024-02-09

5. A Hybrid Paillier Encryption and Randomized Response Technique Model for Surveying Sensitive Questions with Binary Response;Journal of Statistical Theory and Practice;2023-12-27

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