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An optional
unrelated question RRT model
Jeong S. Sihm, Anu Chhabra and Sat N. Gupta
Vol. 9 (2016), No. 2, 195–209
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Abstract |
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We propose a modified unrelated question randomized response technique (RRT) model which allows respondents the option of answering a sensitive question directly without using the randomization device if they find the question nonsensitive. This situation has been handled before by Gupta, Tuck, Spears Gill, and Crowe using the split sample approach. In this work we avoid the split sample approach, which requires larger total sample size. Instead, we estimate the prevalence of the sensitive characteristic by using an optional unrelated question RRT model, but the corresponding sensitivity level is estimated from the same sample by using the traditional binary unrelated question RRT model of Greenberg, Abul-Ela, Simmons, and Horvitz. We compare the simulation results of this new model with those of the split-sample based optional unrelated question RRT model of Gupta et al. and the simple unrelated question RRT model of Greenberg et al. Computer simulations show that the new binary response and quantitative response models have the smallest variance among the three models when they have the same sample size. |
Keywords
optional randomized response models, unrelated questions
randomized response models, parameter estimation,
simulation study
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Mathematical Subject Classification 2010
Primary: 62-02, 62-04, 62D05
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Milestones
Received: 21 November 2013
Accepted: 20 March 2014
Published: 2 March 2016
Communicated by Kenneth S. Berenhaut
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Authors |
| Jeong S. Sihm | |
| Department of Mathematics and
Statistics The University of North Carolina at Greensboro 317 College Ave Greensboro, NC 27412 United States |
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| Anu Chhabra | |
| Department of Mathematics University of Delhi Delhi 110052 India |
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| Sat N. Gupta | |
| Department of Mathematics and
Statistics University of North Carolina at Greensboro 317 College Ave Greensboro, NC 27412 United States |
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