A new estimator of proportion with a linear function using data from two-decks randomized response model

Jayaraj, Augustus; Sedory, Stephen A.; Singh, Sarjinder; Odumade, Oluseun

doi:10.1080/03610926.2017.1321764

Cited by 2 publications

(2 citation statements)

References 28 publications

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“…Lee et al (); Abdelfatah and Mazloum (, ); Batool and Shabbir (); Arnab and Shangodoying (); G.‐S. Lee et al (); Arnab and Thuto (); Batool, Shabbir, and Hussain (); Jayaraj, Sedory, Singh, and Odumade (); and Fox (). Chaudhuri () has contributed a special issue on randomized response, which includes several improvements in different directions on this topic.…”

Section: Odumade and Singh Way Of Utilizing Two Decksmentioning

confidence: 99%

Unrelated question model with two decks of cards

Sedory

Singh

Olanipekun

et al. 2020

Statistica Neerlandica

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Section: Odumade and Singh Way Of Utilizing Two Decksmentioning

confidence: 99%

Unrelated question model with two decks of cards

Sedory

Singh

Olanipekun

et al. 2020

Statistica Neerlandica

Self Cite

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“…A recent list of key references to the theory and practice of randomized response sampling are due to Fox (2016); Fox and Tracy (1986); Chaudhuri, Christofides, and Rao (2016); Chaudhuri and Christofides (2013); and Chaudhuri (2011). Some thoughtful improvements of the Warner (1965) model can be found in Gjestvang and Singh (2006), Su et al (2015, 2017), Lee et al (2016), van den Hout et al (2007), Jayaraj et al (2018), and Singh and Sedory (2011, 2012) among others. Blair et al (2015) wrote a review article on RRTs.…”

Section: Introductionmentioning

confidence: 99%

A Theory of Higher Order Interactions Between Sensitive Variables: Empirical Evidences and an Application to a Variety of Smoking

Olanipekun

Zhao

Wang

et al. 2021

Sociological Methods & Research

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In carrying out surveys involving sensitive characteristics, randomized response models have been considered among the best techniques since they provide the maximum privacy protection to the respondents and procure honest responses. Over the years, researchers have carried out studies on the estimation of proportions of the population possessing sensitive characteristics. However, there is a paucity of research studies that have addressed higher order interactions between these sensitive characters. In this article, we develop a new theory based on three proposed randomized response models which we name as: simple model, semi-crossed model, and fully crossed model. Twenty-one new unbiased estimators of seven parameters are introduced, their variance expressions are derived, and unbiased estimators of variances are developed. The three models are compared under various values of the parameters by computing the percent relative efficiency of one model over another model. The most efficient model is then applied to study the population proportions of three varieties of smoking habits among students, and their first- and second-order interactions. The last four sections (Ninth to Twelfth) are verifications of theoretical results using the Cramer–Rao lower bounds of variances for the developed 21 new estimators in randomized response sampling.

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A new estimator of proportion with a linear function using data from two-decks randomized response model

Cited by 2 publications

References 28 publications

Unrelated question model with two decks of cards

Unrelated question model with two decks of cards

A Theory of Higher Order Interactions Between Sensitive Variables: Empirical Evidences and an Application to a Variety of Smoking

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