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 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.

• Autores: Kim, Jong-Min; Lee, Gi-Sung; Hong, Ki-Hak; Son, Chang-Kyoon
• Tipo de recurso: Article of journal
• Fecha de publicación: 2017
• Institución: Universidad Nacional de Colombia
• Repositorio: Universidad Nacional de Colombia
• Idioma: spa
• OAI Identifier: oai:repositorio.unal.edu.co:unal/66503
• Acceso en línea: https://repositorio.unal.edu.co/handle/unal/66503; http://bdigital.unal.edu.co/67531/
• Palabra clave: 51 Matemáticas / Mathematics; 31 Colecciones de estadística general / Statistics; Randomized response model; Kuk’s model; Sensitive attribute; Stratified sampling; Stratified double sampling; modelo Kuk ajustado; modelo de respuesta aleatorizada; atributos sensibles; muestreo doble estratificado; muestreo estratificado
• Rights: openAccess
• License: Atribución-NoComercial 4.0 Internacional