Mean Estimation of Sensitive Variables Under Non-response and Measurement Errors Using Optional RRT Models
Author:
Publisher
Springer Science and Business Media LLC
Subject
Statistics and Probability
Link
http://link.springer.com/content/pdf/10.1007/s42519-020-00135-2.pdf
Reference28 articles.
1. Ahmed S, Shabbir J, Gupta S (2017) Use of scrambled response model in estimating the finite population mean in presence of non-response when coefficient of variation is known. Commun Stat Theory Methods 46(17):8435–8449
2. Audu A, Singh R, Khare S, Dauran NS (2020) Almost unbiased estimators for population mean in the presence of non-response and measurement error. J Stat Manag Syst. https://doi.org/10.1080/09720510.2020.1759209
3. Bhushan S, Pandey AP (2019) An efficient estimation of population mean under non-response. Commun Stat Appl Methods 26:11–25
4. Bhushan S, Pandey AP (2020) An efficient estimation procedure for the population mean under non-response. Statistica 79(4):363–378
5. Diana G, Perri PF (2011) A class of estimators for quantitative sensitive data. Stat Pap 52:633–650
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1. Estimation of finite population mean of a sensitive variable using three-stage optional RRT in the presence of non-response and measurement errors;Journal of Statistical Computation and Simulation;2024-06-04
2. Improved estimator for the estimation of sensitive variable using ORRT models;Research in Statistics;2024-02-27
3. Quantify the Impact of Non-Response and Measurement Error of Sensitive Variable(s) under Two-Phase Sampling employing ORRT Models;Communications in Advanced Mathematical Sciences;2023-12-25
4. Applying ORRT for the estimation of population variance of sensitive variable;Communications in Statistics - Simulation and Computation;2023-12-20
5. Evaluating the Effect of Measurement Error Under Randomized Response Techniques of the Sensitive Variable in Successive Sampling;Proceedings of the National Academy of Sciences, India Section A: Physical Sciences;2023-08-10
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