TY - JOUR
T1 - Sample surveys with sensitive questions
T2 - A nonrandomized response approach
AU - Tan, Ming T.
AU - Tian, Guo Liang
AU - Tang, Man Lai
N1 - Funding Information:
Ming T. Tan is Professor, Division of Biostatistics, University of Maryland Greenebaum Cancer Center, and Department of Epidemiology and Preventive Medicine, 10 South Pine Street, Baltimore, MD 21201 (E-mail: [email protected]). Guo-Liang Tian is Associate Professor, Department of Statistics and Actuarial Science, The University of Hong Kong, Pokfulam Road, Hong Kong, P. R. China. (E-mail: [email protected]). Man-Lai Tang is Associate Professor, Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, P. R. China. (E-mail: [email protected]). The authors thank the editor, an associate editor, and a referee for their comments and suggestions. The research of M. T. Tan was supported partially by NIH grant RO3CA119758. The research of M. L. Tang was fully supported by a grant (project no. HKBU261508) from the Research Grant Council of the Hong Kong Special Administrative Region.
PY - 2009/2
Y1 - 2009/2
N2 - Since the Warners randomized response (RR) model to solicit sensitive information was proposed in 1965, it has been used and extended in a broad range of surveys involving sensitive questions. However, it is limited, for example, by a lack of reproducibility and trust from the interviewees as well as higher cost due to the use of randomizing devices. Recent developments of the alternative non-randomized response (NRR) approach have shown the promise to alleviate or eliminate such limitations. However, the efficiency and feasibility of the NRR models have not been adequately studied. This article introduces briefly the NRR approach, proposes several new NRR models, compares the efficiency of the NRR and RR models and studies the feasibility of the NRR models. In addition, we propose the concept of the degree of privacy protection between the NRR model and the Warner model to reflect the extent the privacy is protected. These studies show that not only the NRR approach is free of the limitations of the randomized approach but also the NRR model actually increases the relative efficiency and the degree of privacy protection. Thus, the non-randomized response approach offers an attractive alternative to the randomized response ap.
AB - Since the Warners randomized response (RR) model to solicit sensitive information was proposed in 1965, it has been used and extended in a broad range of surveys involving sensitive questions. However, it is limited, for example, by a lack of reproducibility and trust from the interviewees as well as higher cost due to the use of randomizing devices. Recent developments of the alternative non-randomized response (NRR) approach have shown the promise to alleviate or eliminate such limitations. However, the efficiency and feasibility of the NRR models have not been adequately studied. This article introduces briefly the NRR approach, proposes several new NRR models, compares the efficiency of the NRR and RR models and studies the feasibility of the NRR models. In addition, we propose the concept of the degree of privacy protection between the NRR model and the Warner model to reflect the extent the privacy is protected. These studies show that not only the NRR approach is free of the limitations of the randomized approach but also the NRR model actually increases the relative efficiency and the degree of privacy protection. Thus, the non-randomized response approach offers an attractive alternative to the randomized response ap.
KW - Nonrandomized response models
KW - Randomized response technique
KW - Randomizing device
KW - Sensitive questions
KW - Warner model
UR - http://www.scopus.com/inward/record.url?scp=63549110682&partnerID=8YFLogxK
U2 - 10.1198/tast.2009.0002
DO - 10.1198/tast.2009.0002
M3 - Journal article
AN - SCOPUS:63549110682
SN - 0003-1305
VL - 63
SP - 9
EP - 16
JO - American Statistician
JF - American Statistician
IS - 1
ER -