Papers by Dr. Preeti Patidar (Assistant Professor, SSBSR)
Journal of Modern Applied Statistical Methods
In this paper motivated by Lee et al (2013) and Singh et al (2017,2020), we have suggested the es... more In this paper motivated by Lee et al (2013) and Singh et al (2017,2020), we have suggested the estimation procedures of mean number of persons possessing sensitive attribute using Narjis and Shabbir (2020) randomized response model for the population which comprises of some clusters and the population is stratified with some clusters in each stratum. The estimator for the mean number of persons possessing sensitive attribute under a Poisson distribution, its variance, and the estimator of the variance are proposed under two-stage and stratified two-stage sampling schemeswhen the parameter of the rare sensitive attribute is pretended to be known and unknown. We employ the sampling scheme with probability proportional to size to select the first-stage units and simple random sampling with replacement to select the second-stage units.Theperformance of the suggested estimation procedures are demonstrated through numerical illustration over Singh and Suman (2019) estimators.
Model Assisted Statistics and Applications, Jul 2, 2021
This paper suggests a new randomized response model useful for gathering information on quantitat... more This paper suggests a new randomized response model useful for gathering information on quantitative sensitive variable such as drug usage, tax evasion and induced abortions etc. The resultant estimator has been found to more efficient than the estimator of the Saha (2007) under some realistic conditions. We have illustrated results numerically.
Pakistan Journal of Statistics and Operation Research
In this paper we have suggested a class of estimators of population mean of sensitive variable un... more In this paper we have suggested a class of estimators of population mean of sensitive variable under optional randomized response technique as reported in Gupta et al  (2014). We have obtained the mean squared error (MSE) of the suggested class of estimators up to the first order of approximation. The optimum conditions are obtained at which the (MSE) of the proposed class of estimators is minimum. An empirical study is carried out to show the performance of the suggested class of estimators over existing estimators .It is found that the performance of proposed class of estimators is better than the existing estimators including Grover and Kaur (2019).
Journal of Applied Mathematics and Statistics, 2016
This paper proposes a class of estimators for population total Y using two auxiliary variables. I... more This paper proposes a class of estimators for population total Y using two auxiliary variables. In addition to many, it is identified that the proposed class of estimators includes the estimators due to Singh, M.P. (1967), Srivastava, S.K. (1967), Srivastava, V.K. (1974), Singh, H.P. (1986), Prasad, B. (1989) and Gandge et al. (1993). To the first degree of approximation, the bias and mean squared error of the proposed class of estimators have been obtained. The optimum condition is obtained in which the proposed class of estimators has minimum mean squared error. The superiority of the proposed class of estimators is also discussed. An empirical study is carried in support of the present study.
Model Assisted Statistics and Applications, 2021
This paper suggests a new randomized response model useful for gathering information on quantitat... more This paper suggests a new randomized response model useful for gathering information on quantitative sensitive variable such as drug usage, tax evasion and induced abortions etc. The resultant estimator has been found to more efficient than the estimator of the Saha (2007) under some realistic conditions. We have illustrated results numerically.
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Papers by Dr. Preeti Patidar (Assistant Professor, SSBSR)