Estimación de atributos sensibles usando un mecanismo de aleatorización estratificado de kuk

Translated title of the contribution: Estimation of sensitive attributes using a stratified kuk randomization device

Lee Gi-Sung, Hong Ki-Hak, Kim Jong-Min, Son Chang-Kyoon

    Research output: Contribution to journalArticlepeer-review

    Abstract

    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.

    Translated title of the contributionEstimation of sensitive attributes using a stratified kuk randomization device
    Original languageSpanish
    Pages (from-to)29-44
    Number of pages16
    JournalRevista Colombiana de Estadistica
    Volume40
    Issue number1
    DOIs
    StatePublished - 2017

    Bibliographical note

    Funding Information:
    This research was supported by the Basic Science Research Program of the National Research Foundation of Korea (NRF), which is funded by the Ministry of Science, ICT, and Future Planning (2015R1A2A2A 01003699). The corresponding author of this research is Assistant professor Son Chang-Kyoon.

    Keywords

    • Adjusted kuk model
    • Randomized response model
    • Sensitive attribute
    • Stratified double sampling
    • Stratified sampling

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