title: Recent Advances for Non-randomized Response Techniques--The Parallel Model, A Variant and An Extension
                              
Guo-Liang Tian, PhD
Associate Professor in Statistics
Dept of Statistics and Actuarial Science
The University of Hong Kong

Date & Time ：  2010 / 10/ 20 , 2pm-3pm
Venue： Room 107,  Li Ren Building
Organizer：Institute of Biostatistics (Tel：55665561,Prof.Yueqing Hu), School of Life Sciences

ABSTRACT
Since the randomized response model to solicit sensitive information was proposed by Warner in 1965, it has been used in a broad range of statistical applications for surveys involving sensitive questions. However, the Warner model is limited in several ways including (i) a lack of reproducibility; (ii) a lack of trust from the interviewees; (iii) a higher cost due to the use of randomizing devices; and (iv) narrow range of applications. Recent developments of the non-randomized approach have shown the promise to alleviate or eliminate these limitations. Following a brief introduction of the Warner model and other randomized response model, we review the non-randomized crosswise model and the non-randomized triangular model. However, the crosswise and triangular models cannot be applied to situation where both {Y=0} and {Y=1} are sensitive. In addition, the triangular model still has a lower efficiency for some cases. Therefore, this article proposes a new non-randomized response model called the parallel model and corresponding statistical analysis methods. Theoretical and numerical comparisons show that the randomized parallel model is more efficient than the triangular model for some cases. A variant of the parallel model and a multi-category parallel model are also developed.