Estimating prevalence of induced abortion and multiple sexual partners using improved randomized response technique for two sensitive attributes

Ewemooje, Olusegun Sunday; Amahia, G. N.; Adebola, Femi Barnabas

doi:10.1080/23737484.2017.1398057

Cited by 8 publications

(7 citation statements)

References 20 publications

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“…However, contrary to what was reported by Jann et al, (2012) where Crosswise Model (CM) produced higher estimate with higher standard error, the proposed method produced higher estimate with lower standard error as against the DM. Hence, the proposed model performs better than the DM in line with earlier works of Jann et al (2012), Ewemooje et al, (2017), Cobo et al, (2016) and Ewemooje et al, (2019b).…”

Section: Application Of the Proposed Modelsupporting

confidence: 84%

“…They found out that RRM elicited more socially undesirable answers than direct questioning. Ewemooje et al, (2017) also used Improved Randomized Response Technique for two sensitive attributes (IRRT2) to show that RRM performs better that Direct Method of questioning (DM) by estimating prevalence of induced abortion and multiple sexual partners. Cobo et al, (2016) used RRM to investigate cannabis use by Spanish University students and then compared the result with DM.…”

Section: Introductionmentioning

confidence: 99%

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Unbiased estimator modeling in unrelated dichotomous randomized response

Adediran

Adebola

Ewemooje

2020

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The unrelated design has been shown to improve the efficiency of a randomized response method and reduces respondents' suspicion. In the light of this, the paper proposes a new Unrelated Randomized Response Model constructed by incorporating an unrelated question into the alternative unbiased estimator in the dichotomous randomized response model proposed by Ewemooje in 2019. An unbiased estimate and variance of the model are thus obtained. The variance of the proposed model decreases as the proportion of the sensitive attribute π_A and the unrelated attribute π_U increases, in contrast to the earlier Ewemooje model, whose variance increases as the proportion of the sensitive attribute increases. The relative efficiency of the proposed model over the earlier Ewemooje model decreases as π_U increases when 0.1≤π_A≤ 0.3 and increases as π_U increases when 0.35≤π_A≤ 0.45. Application of the proposed model also revealed its efficiency over the direct method in estimating the prevalence of examination malpractices among university students;the direct method gave an estimate of 19.0%, compared to the proposed method's estimate of 23.0%. Hence, the proposed model is more efficient than the direct method and the earlier Ewemooje model as the proportion of people belonging to the sensitive attribute increases.

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Section: Application Of the Proposed Modelsupporting

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Unbiased estimator modeling in unrelated dichotomous randomized response

Adediran

Adebola

Ewemooje

2020

Statistics in Transition New Series

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“…Christofides [16] introduced the RR model to estimate the proportions of two dependent sensitive attributes at the same time. Studies on estimation of two dependent sensitive attributes have been reported by Lee et al [17]; Batool and Shabbir [18]; Ewemooje and Amahia [19]; Ewemooje [20]; and Ewemooje et al [21].…”

Section: Introductionmentioning

confidence: 99%

Partial Randomized Response Model for Simultaneous Estimation of Means of Two Sensitive Variables

Narjis

Shabbir

Onyango

2022

Mathematical Problems in Engineering

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In this study, a new partial randomized response model (RRM) has been proposed for estimating the population mean of two quantitative sensitive variables simultaneously. The utility of proposed model under stratification is also explored. The efficiency comparisons of the proposed model under simple and stratified random sampling are carried out numerically. A real data set was collected through direct questioning, proposed partial RRM and competitor randomized device from the students of statistics and animal sciences departments of Quaid-I-Azam University Islamabad, Pakistan. The performance of the proposed partial RRM is better than competitor RRM under simple and stratified random sampling.

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“…Since then, a lot of work has been done to improve Warner [1] work by modifying and developing new Randomized Response Techniques (RRT). These include; Mangat and Singh [2], Kim and Warde [3], Adebola et al [4], Ewemooje and Amahia [5,6], Singh and Gorey [7], Ewemooje [8], Ewemooje et al [9,10] and so on. Adebola et al [11] proposed a Hybrid Tripartite Randomized Response Technique (HTRRT) to take care of respondents who may not choose either "yes" or "no" which led to their third option called "undecided" response.…”

Section: Introductionmentioning

confidence: 99%