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http://dx.doi.org/10.5351/CKSS.2003.10.1.247

The Three-Stage Cluster Randomized Response Model for Obtaining Sensitive Information  

Lee, Gi Sung (Division of Computer and Information Science, Woosuk University)
Hong, Ki Hak (Department of Computer Science, Dongshin University)
Son, Chang Kyoon (Department of Computer Science, Dongshin University)
Jung, Young Mee (Department of Statistics, Dongguk University)
Publication Information
Communications for Statistical Applications and Methods / v.10, no.1, 2003 , pp. 247-256 More about this Journal
Abstract
In this study, we systemize the theoretical validity for applying RRM to three-stage cluster sampling method and derive the estimate and it's variance of sensitive parameter. We derive the minimum variance form under the optimal values of the subsample sizes when the costs are fixed. Under the some given precision, we obtain the optimal values of the subsample sizes and derive the minimum cost form by using them. We apply the three-stage cluster RRM to field survey and suggest some necessary points for practical use.
Keywords
Sensitive question; Randomized response model; Three-stage cluster sampling; Field survey;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 /
[ Fox, J.A.;Tracy, P.E. ] / Randomized Response : A Method for Sensitive Survey
2 /
[ Ryu, J.B.;Hong, K.H.;Lee, G.S. ] / Randomized Response Model
3 A Practical Method of Randomized Response Technique /
[ Ryu, J.B.;Lee, K.O.;Lee, G.S. ] / The Korean Journal of Applied Statistics   과학기술학회마을
4 /
[ Chaudhuri, A.;Mukerjee, R. ] / Randomized Response : Theory and Techniques
5 The Unrelated Question Randomized Response Model : Theoretical Framework /
[ Greenberg, B.G.;Abul-Ela;Abdel-Latif A.;Simmons, W.R.;Horvitz, D.G. ] / Journal of the American Statistical Association   DOI   ScienceOn
6 Two-Stage Cluster Randomized Response Model /
[ Lee, G.S.;Hong, K.H. ] / The Korean Communications in Statistics
7 Randomized Response ; A Survey Technique for Eliminating Evasive Answer Bias /
[ Warner, S.L. ] / Journal of the American Statistical Association   DOI   ScienceOn