A randomized response model for sensitive attribute with privacy measure using Poisson distribution

Singh, Chandraketu; Singh, G. N.; Kim, Jong Min

doi:10.1016/j.asej.2021.03.006

Cited by 9 publications

(7 citation statements)

References 13 publications

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“…El aporte de la iglesia también es importante frente a este problema, y las autoridades de la universidad en coordinación con la iglesia se deben implementar charlas sobre estos temas sensibles. El MRA de Odumade y Singh, y otros modelos similares son mejores cuando el tema es altamente más sensible o comprometedor como se muestra en el presente estudio (Matos & Solano, 2016;Chandraketu et al, 2021;Solano et al, 2010a).…”

Section: Discussionunclassified

Modelo de respuesta aleatoria sobre el comportamiento sexual y consumo de alcohol de los estudiantes de una universidad pública, Lima-Perú

et al. 2022

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La presente investigación tuvo como objetivo identificar el comportamiento sexual y consumo de alcohol de los discentes universitarios, matriculados en la Facultad de Ciencias Matemáticas de una universidad pública, durante el primer periodo académico del año 2016. Se utilizó el modelo de respuesta aleatoria. Este estudio se desarrolló dentro de un enfoque cuantitativo, no experimental y de diseño transversal, porque se desarrolló en el primer semestre del 2016. El diseño muestral que se consideró fue aleatorio estratificado. Para estimar el tamaño de muestra se usó un límite del error de estimación de 0.05 y un nivel de confianza del 95%, y la información de los discentes otorgada por la jefa de matrícula de la facultad. El tamaño de muestra fue de 306 alumnos. Utilizando el modelo propuesto por Odumade y Singh, se consideró el mecanismo aleatorizado de dos barajas de tarjetas. Entre los resultados tenemos que el 57% de los entrevistados manifiesta que han tenido relaciones sexuales sin utilizar preservativos, el 51% expresa que han consumido bebidas alcohólicas hasta el estado de ebriedad; el 46% revela que ha tenido relaciones sexuales después de consumir alcohol y el 41% de los entrevistados declara que ha tenido sexo sin protección después de consumir alcohol.

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Section: Discussionunclassified

Modelo de respuesta aleatoria sobre el comportamiento sexual y consumo de alcohol de los estudiantes de una universidad pública, Lima-Perú

et al. 2022

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“…Singh and Singh [18] offered a technique for finding the population fraction of a stigmatized characteristic, making use of very well-known distribution that is negative binomial distribution for his work. Singh et al [19] projected a three-stage randomized response model, making use of poisson distribution. Halim et al [20] derived the transition matrices of the conditional misclassification probabilities of multiple above mentioned models and also worked on finding the association of variables while taking RR into account.…”

Section: Survey Sampling and Randomized Responsementioning

confidence: 99%

“…Replacing ∂θ i /∂β from (19) and θ from (18)in the derivative of the log likelihood function ∂ ln L/∂β from (5), we get:…”

Section: Let Us First Find ∂θmentioning

confidence: 99%

Estimation of Hidden Logits Using Several Randomized Response Techniques

Halim,

Arshad,

Alomair

et al. 2023

Symmetry

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In survey sampling, we aspire to obtain sound and consistent responses, which are not achieved while dealing with sensitive issues. Frequently, respondents give elusive responses to sensitive questions, so we employ randomized response techniques that facilitate finding an appropriate proportion of socially sensitive characteristics. In the present study, we proposed a hidden logit estimation method using Huang, Warner, and Mangat’s randomized response techniques. This study depicts that the estimates become closer to the standard logits as the values of p increase. We found that the hidden logit estimates obtained by the Huang randomized response technique were nearer to the parametric values, in contrast to the other existing techniques, and we demonstrate an increase in accuracy as well. The simulation-based AIC and SIC values are used to assess model performance. We found that the Huang model is the best model for the proposed hidden logit method. This paper contributes towards the application of logistic models in the case of sensitive or socially stigmatized issues.

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“…Recently, Singh et al [ 25 ] developed two new quantitative randomized response models which were shown to be better than the existing models in terms of efficiency as well as privacy protection level. In another study, Singh et al [ 26 ] utilized Poisson distribution to develop a three-stage randomized response model which helps in estimating the mean number of persons having a sensitive attribute. The Singh et al [ 26 ] model improved the efficiency of the existing models.…”

Section: Introductionmentioning

confidence: 99%

“…In another study, Singh et al [ 26 ] utilized Poisson distribution to develop a three-stage randomized response model which helps in estimating the mean number of persons having a sensitive attribute. The Singh et al [ 26 ] model improved the efficiency of the existing models.…”

Section: Introductionmentioning

confidence: 99%

A neutral comparative analysis of additive, multiplicative, and mixed quantitative randomized response models

Azeem

Ali

2023

PLoS ONE

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In survey sampling, the randomized response technique is a useful tool to collect reliable data in many fields including sociology, education, economics, and psychology etc. Over the past few decades, many variants of quantitative randomized response models have been developed by researchers. The existing literature on randomized response models lacks a neutral comparative study of different models to help the practitioners choose the appropriate model for a given practical problem. In most of the existing studies, the authors tend to show only the favorable results by hiding the cases where their suggested models are inferior to the existing models. This approach often leads to biased comparisons which may badly misguide the practitioners when choosing a randomized response model for a practical problem at hand. This paper attempts a neutral comparison of six existing quantitative randomized response models using separate as well as joint measures of respondent-privacy and model-efficiency. The findings suggest that one model may perform better than the other model in terms of efficiency but may perform worse when other metrics of model quality are taken into account. The current study guides practitioners in choosing the right model for a given problem under a particular situation.

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A randomized response model for sensitive attribute with privacy measure using Poisson distribution

Cited by 9 publications

References 13 publications

Modelo de respuesta aleatoria sobre el comportamiento sexual y consumo de alcohol de los estudiantes de una universidad pública, Lima-Perú

Modelo de respuesta aleatoria sobre el comportamiento sexual y consumo de alcohol de los estudiantes de una universidad pública, Lima-Perú

Estimation of Hidden Logits Using Several Randomized Response Techniques

A neutral comparative analysis of additive, multiplicative, and mixed quantitative randomized response models

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