A regression estimator for finite population mean of a sensitive variable using an optional randomized response model. Issue 3 (16th March 2017)

• Record Type: Journal Article
• Authors: Gupta, Sat; Kalucha, Geeta; Shabbir, Javid
• Is Part Of: Communications in statistics. Volume 46:Issue 3(2017)
• Page Start: 2393
• Page End: 2405
• Publication Date: 2017-03-16
• Subjects: Auxiliary Information -- Mean square error -- Optional randomized response technique -- Ratio estimator -- Regression estimator.; 62D05; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2015.1044614
• Languages: English
• ISSNs: 0361-0918

Abstract

ABSTRACT: Kalucha et al. (Kalucha G., Gupta S., Dass B. K. (accepted). Ratio estimation of finite population mean using optional randomized response models. Journal of Statistical Theory and Practice ) introduced an additive ratio estimator for finite population mean of a sensitive variable in simple random sampling without replacement and showed that this estimator performs better than the ordinary mean estimator based on an optional randomized response technique (RRT). In this paper, we introduce a regression estimator that performs better than the ratio estimator even for the modest correlation between the study and the auxiliary variables. A comparison of the proposed estimator with the corresponding ratio estimator and the ordinary RRT mean estimator is carried out theoretically, and is also illustrated with a simulation study.