scholarly journals A Multi-proportion Randomized Response Model Using the Inverse Sampling

2014 ◽  
pp. 199-218
Author(s):  
Marcella Polisicchio ◽  
Francesco Porro
Keyword(s):  
Response Model ◽  
Randomized Response ◽  
Inverse Sampling ◽  
Randomized Response Model

scholarly journals An Additive Stratified Quantitative Attribute Randomized Response Model

2014 ◽  
Vol 27 (2) ◽  
pp. 239-247
Author(s):  
Gi-Sung Lee ◽  
Seung-Chul Ahn ◽  
Ki-Hak Hong ◽  
Chang-Kyoon Son
Keyword(s):  
Response Model ◽  
Randomized Response ◽  
Randomized Response Model

scholarly journals A Stratified Multi-proportions Randomized Response Model

2015 ◽  
Vol 28 (6) ◽  
pp. 1113-1120 ◽  
Author(s):  
Gi-Sung Lee ◽  
Kyung-Soon Park
Keyword(s):  
Response Model ◽  
Randomized Response ◽  
Randomized Response Model

scholarly journals A Remark on Gupta, Gupta and Singh Optional Randomized Response Model

2019 ◽  
Vol 15 (1) ◽  
pp. 43-73
Author(s):  
H. P. Singh ◽  
S. M. Gorey
Keyword(s):  
Response Model ◽  
Randomized Response ◽  
Numerical Illustration ◽  
The Mean ◽  
Randomized Response Model

Abstract Gupta et al (2002) suggested an optional randomized response model under the assumption that the mean of the scrambling variable S is ‘unity’ [i.e. µs = 1]. This assumption limits the use of Gupta et al’s (2002) randomized response model. Keeping this in view we have suggested a modified optional randomized response model which can be used in practice without any supposition and restriction over the mean (µs) of the scrambling variables S. It has been shown that the estimator of the mean of the stigmatized variable based on the proposed optional randomized response sampling is more efficient than the Eicchorn and Hayre (1983) procedure and Gupta et al’s (2002) optional randomized technique when the mean of the scrambling S is larger than unity [i.e. µs > 1]. A numerical illustration is given in support of the present study.

An improved randomized response model: estimation of mean

2009 ◽  
Vol 36 (12) ◽  
pp. 1361-1367 ◽  
Author(s):  
Christopher R. Gjestvang ◽  
Sarjinder Singh
Keyword(s):  
Model Estimation ◽  
Response Model ◽  
Randomized Response ◽  
Randomized Response Model
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