28 research outputs found
A Proficient Two-Stage Stratified Randomized Response Strategy
No full textA stratified randomized response model based on R. Singh, Singh, Mangat, and Tracy (1995) improved two-stage randomized response strategy is proposed. It has an optimal allocation and large gain in precision. Conditions are obtained under which the proposed model is more efficient than R. Singh et al. (1995) and H. P. Singh and Tarray (2015) models. Numerical illustrations are also given in support of the present study
An Improved Estimation Procedure of the Mean of a Sensitive Variable Using Auxiliary Information
No full textA stratified Mangat and Singh’s optional randomized response model using proportional and optimal allocation
No full textThis paper suggests a stratified optional randomized response model based on Mangat and Singh (1994) model that has proportional and optimal allocation and larger gain in efficiency. Numerically it is found that the suggested model is more efficient than Kim and Warde (2004) stratified randomized response model and Mangat and Singh (1994) model. Graphical representations are also given in support of the present study
A New Optimal Orthogonal Additive Randomized Response Model Based on Moments Ratios of Scrambling Variable
No full textNew Procedures of Estimating Proportion and Sensitivity Using Randomized Response in a Dichotomous Finite Population
No full textThe problem of estimating the population proportion possessing a sensitive attribute using simple random sampling with replacement (SRSWR) is advocated. Two new procedures are proposed. The suggested models are more efficient than the Huang (2004) randomized response technique under some realistic conditions. Numerical and graphic illustrations are given
Bayesian Analysis and Reliability Estimation of Generalized Probability Distributions
No full textThis edited volume entitled “Bayesian Estimation and Reliability Estimation of Generalized Probability Distributions” is being published for the benefit of researchers and academicians. It contains ten different chapters covering a wide range of topics both in applied mathematics and statistics. The proofs of various theorems and examples have been given with minute details. During the preparation of the manuscript of this book, the editor has incorporated the fruitful academic suggestions provided by Dr. Peer Bilal Ahmad, Dr. Sheikh Parvaiz Ahmad, Dr. J. A. Reshi, Dr. Tanveer Ahmad Tarray, Dr. Kowsar Fatima, Dr. Ahmadur Rahman, Dr. Showkat Ahmad Lone, Mudasir Sofi, Uzma Jan, Aaliya Syed, and Dr. Humaira Sultan. It is expected to have good popularity due to its usefulness among its readers and users
A randomization device for estimating a rare sensitive attribute in stratified sampling using Poisson distribution
No full textAn alternative to Kim and Warde’s mixed randomized response technique
No full textThe paper proposes two mixed randomized response techniques as an alternative to the Kim and Warde’s (2005) randomized response technique. The properties of the models have been studied and found that the proposed mixed randomized response models are better than the Kim and Warde’s (2005) mixed randomized response models in some realistic situations. We extend the proposed model to stratified sampling. Numerical illustration is given in support of the present study
A simple way of improving the Bar–Lev, Bobovitch and Boukai Randomized response model
No full textEichhorn & Hayre (1983) considered a randomized response procedure suitable for estimating the mean response, when the sensitive variable under investigation is quantitative in nature. They have obtained an estimate for the mean of the quantitative response variable under investigation and studied its properties. Bar–Lev et al. (2004) have suggested an alternative procedure, which use a design parameter (controlled by the experimenter) that generalizes Eichhorn & Hayre’s (1983) results. They have also proved that the estimator proposed by them has uniformly smaller variance as compared to that of Eichhorn & Hayre (1983) in certain condition. In this paper we have suggested a simple procedure of improving the Eichhorn & Hayre (1983) and Bar–Lev et al. (2004) models along with its properties. It has been shown that the proposed procedure is uniformly better than Bar–Lev et al. (2004) procedure. The proposed procedure is also uniformly better than Eichhorn and Hayre’s (1983) procedure under the same condition in which the Bar–Lev et al.’s (2004) procedure is more efficient than Eichhorn & Hayre’s (1983) procedure. Numerical illustration is given in support of the present study
