An Improved Two-stage Randomized Response Model for Estimating the Proportion of Sensitive Attribute

Narjis, Ghulam; Shabbir, Javid

doi:10.1177/00491241211009950

Cited by 7 publications

(2 citation statements)

References 20 publications

(46 reference statements)

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“…The work of Narjis and Shabbir [16] and Hsieh et al [17] is also to be noted in the case of the use of two-stage RR models in order to find the commonness of a sensitive characteristic. 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.…”

Section: Survey Sampling and Randomized Responsementioning

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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Section: Survey Sampling and Randomized Responsementioning

confidence: 99%

Estimation of Hidden Logits Using Several Randomized Response Techniques

Halim,

Arshad,

Alomair

et al. 2023

Symmetry

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“…To enhance the tendency for respondents to truthfully answer sensitive questions, the randomized response technique (RRT) and its modifications have been proposed by Warner (1965) and subsequent authors (Greenberg et al, 1969;Horvitz et al, 1967;Kuk, 1990;Singh et al, 2000;Gjestvang and Singh, 2006;Narjis, 2021). In short, the RRT makes the respondents respond to sensitive issues through some random device (such as coin, card, or dice) whose outcome is blind to the interviewer.…”

Section: Introductionmentioning

confidence: 99%

Regression Analysis of Randomized Response Event Time Data

Wen¹,

Chen²

2025

STAT SINICA

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The randomized response technique (RRT), including the related-question RRT of Warner (1965) and the unrelated-question RRT of Greenberg et al. (1969), has been utilized to reduce underreporting of sensitive characteristics in survey studies by enhancing privacy protection. Currently, the RRT is mainly applied for prevalence estimation of some sensitive event. This work extends the application of the RRT to the analysis of time-to-event outcome. Since event time data collected from surveys are usually subject to case-I interval censoring so that only "current status" data regarding the occurrence of the event by the examination time are available, we focus on the current status (case-I interval censored) event time data collected by the RRT. Based on such data, we propose a semiparametric maximum likelihood estimation procedure for the event time distribution given the covariates, which is assumed to follow a general class of semiparametric transformation models characterized by a parametric function for the relationship between the event time and the covariates, as well as an unspecified baseline function. The asymptotic theory, including the consistency and asymptotic normality, for the proposed estimation is developed, and its finite sample properties are examined by simulation studies. We apply the proposed method to a set of current status data surveyed by the RRT to make statistical inferences on the time to the incidence of extramarital relations since marriage.

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An Improved Two-Stage Forced Randomized Response Model for Estimating the Proportion of Sensitive Attribute

Tiwari

Pandey

2022

J Indian Soc Probab Stat

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An Improved Two-stage Randomized Response Model for Estimating the Proportion of Sensitive Attribute

Cited by 7 publications

References 20 publications

Estimation of Hidden Logits Using Several Randomized Response Techniques

Estimation of Hidden Logits Using Several Randomized Response Techniques

Regression Analysis of Randomized Response Event Time Data

An Improved Two-Stage Forced Randomized Response Model for Estimating the Proportion of Sensitive Attribute

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