An innovative optimal randomized response model using correlated scrambling variables-Reference-Cited by-同舟云学术

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An innovative optimal randomized response model using correlated scrambling variables

Published:2020-07-25 Issue:15 Volume:90 Page:2823-2839
ISSN:0094-9655
Container-title:Journal of Statistical Computation and Simulation
language:en
Short-container-title:Journal of Statistical Computation and Simulation

Author:

Murtaza Maryam¹²,Singh Sarjinder³^ORCID,Hussain Zawar⁴^ORCID

Affiliation:

1. Department of Mathematics, COMSATS University Islamabad, Wah Campus, Islamabad, Pakistan

2. Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan

3. Department of Mathematics, Texas A&M University-Kingsville, Kingsville, TX, USA

4. Department of Social & Allied Sciences, Cholistan University of Veterinary & Animal Sciences, Bahawalpur, Pakistan

Publisher

Informa UK Limited

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,Modelling and Simulation,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/00949655.2020.1791118

Reference21 articles.

1. Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias

2. Application of the Randomized Response Technique in Obtaining Quantitative Data

3. Additive constants model: A randomized response technique for eliminating evasiveness to quantitative response questions.

4. Scrambled randomized response methods for obtaining sensitive quantitative data

Cited by 7 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 stratified estimation for sensitive variable using correlated scrambling variables;Communications in Statistics - Theory and Methods;2024-04-04

2. An Improved Class of Ratio and Product Estimators Based on ORRT Models;Revista Colombiana de Estadística;2024-01-15

3. Franklin's randomized response model with correlated scrambled variables;Statistica Neerlandica;2023-09-05

4. A neutral comparative analysis of additive, multiplicative, and mixed quantitative randomized response models;PLOS ONE;2023-04-26

5. Using the exponential function of scrambling variable in quantitative randomized response models;Mathematical Methods in the Applied Sciences;2023-04-21

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