Estimation of Sensitive Attributes Using a Stratified Kuk Randomization Device

This paper suggests a stratified Kuk model to estimate the proportion of sensitive attributes of a population composed by a number of strata; this is undertaken  by applying stratified sampling to the adjusted Kuk model. The paper estimates sensitive parameters when the size of the stratum is known...

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Bibliographic Details
Published inRevista Colombiana de Estadística Vol. 40; no. 1; pp. 29 - 44
Main Authors Kim, Jong-Min, Lee, Gi-Sung, Hong, Ki-Hak, Son, Chang-Kyoon
Format Journal Article
LanguageEnglish
Published Bogota Universidad Nacional de Colombia 2017
Subjects
Adjusted Kuk Model
Economic models
Mathematical models
Parameter estimation
Parameter sensitivity
Randomized Response Model
Sampling
Sensitive Attribute
Stratified Double Sampling
Stratified Sampling
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Summary:This paper suggests a stratified Kuk model to estimate the proportion of sensitive attributes of a population composed by a number of strata; this is undertaken  by applying stratified sampling to the adjusted Kuk model. The paper estimates sensitive parameters when the size of the stratum is known by taking proportional and optimal allocation methods into account and then extends to the case of an unknown stratum size, estimating sensitive parameters by applying stratified double sampling and checking the two allocation methods. Finally, the paper compares the efficiency of the proposed model to that of the Su, Sedory  and Singh model and the adjusted Kuk model in terms of the estimator variance.
ISSN:0120-1751
2389-8976
DOI:10.15446/rce.v40n1.53459