学科建设
学科建设
香港大学统计与精算系田国梁副教授学术报告
发布时间:2017-11-27 01:36:03发布作者:admin阅读次数:196

Title:        Recent Advances for Non-randomized Response Techniques: The Parallel Model, A Variant and An Extension

Datetime:       2015-06-30  11:00-12:00AM

Venue:         Room 108,   Wuzhi  Building

Affiliation:    Dept of Statistics and Actuarial Science,  UniversityofHong Kong

Speaker:        Guo-Liang Tian, PhD,Associate Professor

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.

Attachment: A Short Biography of Guo-Liang TIAN