• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.721-729
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• 2000

In this paper, we propose a new conditional randomized response model that has improved the Carr et al.'s model in view of he variance and the protection of privacy of respondents. We show that he suggested model is more effective and protective than the Loynes' model and Carr et al.' model.

• Journal of applied mathematics & informatics
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• v.8 no.1
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• pp.253-260
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• 2001

In this paper we suggest a conditional unrelated question randomized response model by using the Carr et. al.’s model(1982) and Greenberg et. al.’s model(1969). Our model can obtain more comprehensive information about the sensitive character A. We suggest the conditions that make our model efficient compared with models of Greenberg et. al. and Carr et al..

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.33-38
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• 2000

Krishnamoorphy and Raghavarao(1993) invented exact binomial and asymptotically normal test procedures for truthful answering in the repeated randomized response models under the assumption that two repeated response measures are independent. Under the same assumption, Lakshmi and Raghavarao(1992) suggested asymptotic chi-square test for respondents' truthful answering in the same models. In this article we detect the factors and the conditions with which two response variables might be independent, and find the condition for independence in the repeated randomized response models with considering untruthful answer. But, the condition of independence make the randomized model no meaning. Under the assumption of conditional independence between two response variables, we can apply the same logical statements on deriving the tests for truthful answering in the repeated randomized response models as in Krishnamoorphy and Raghavarao(1993).

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2883-2893
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• 2018

We suggest a stratified conditional unrelated question randomized response model to more efficiently estimate a sensitive character A when the population is composed of several strata. In that model, only the respondents who answered "yes" through randomization device which was consisted of a less sensitive character B and a question forcing to answer "yes" respond to our suggested model and we deal with two allocation problems of proportional allocation and optimal one. We expand the suggested model into two sample stratified conditional unrelated question model to cover the case of unknowing unrelated character and deduce minimal variance through optimal sample size of stratum h. Finally, we show that the suggested model is more efficiency than stratified unrelated models and the stratified Carr et al.'s model (1982) under some given conditions, and show numerically that the smaller the values ${\pi}_{h2}$ and ${\pi}_{hy}$, the more efficiency the fit of the model.