Stratified Sampling

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Javid Shabbir - One of the best experts on this subject based on the ideXlab platform.

Masood Anwar - One of the best experts on this subject based on the ideXlab platform.

Housila P. Singh - One of the best experts on this subject based on the ideXlab platform.

  • a randomization device for estimating a rare sensitive attribute in Stratified Sampling using poisson distribution
    Afrika Matematika, 2018
    Co-Authors: Tanveer A Tarray, Housila P. Singh
    Abstract:

    The nitty-gritty of this paper is to estimate the mean of the number of persons possessing a rare sensitive attribute by utilizing the Poisson distribution in Stratified survey Sampling. It is also shown that the proposed models are more efficient than Lee et al.’s (Statistics 47:575–589, 2013) models in both the cases when the proportion of persons possessing a rare unrelated attribute is known and that when it is unknown. Properties of the proposed randomized response models have been studied alongwith recommendations. Numerical illustrations are also given in support of the present study.

  • a randomized response model for estimating a rare sensitive attribute in Stratified Sampling using poisson distribution
    Model Assisted Statistics and Applications, 2015
    Co-Authors: Tanveer A Tarray, Housila P. Singh
    Abstract:

    The crux of this paper is to estimate the mean of the number of persons possessing a rare sensitive attribute based on the Singh et al. (1) randomization device by utilizing the Poisson distribution in Stratified Sampling. This study also deals with the extension of the estimation reported by Singh and Tarray (2) using a Poisson distribution and an unrelated question randomized response model reported in Singh et al. (1). In Stratified Sampling, the estimators are proposed when the parameter of the rare unrelated attribute is known and also when it is unknown. It is shown that the proposed models are more efficient than the model given by Lee et al. (3) in both cases, that is, when the proportion of persons possessing a rare unrelated attribute is known and that when it is unknown. When the sizes of the Stratified populations are not given, other estimators are suggested using Stratified double Sampling. Properties of the proposed randomized response model are studied and recommendations are made.

  • Effect of Measurement Errors on the Separate and Combined Ratio and Product Estimators in Stratified Random Sampling
    Journal of Modern Applied Statistical Methods, 2010
    Co-Authors: Housila P. Singh, Namrata Karpe
    Abstract:

    μ of a study variable Y using auxiliary variable X in Stratified Sampling when the observations are contaminated with measurement errors. The bias and mean squared error of the proposed estimators have been derived under large sample approximation and their properties are analyzed. Generalized versions of these estimators are given along with their properties.

  • a general procedure for estimating the population mean in Stratified Sampling using auxiliary information
    Metron-International Journal of Statistics, 2010
    Co-Authors: Housila P. Singh, Gajendra K Vishwakarma
    Abstract:

    In this paper we have suggested a general procedure for estimating the population mean in Stratified Sampling using auxiliary information. A general class of estimators is defined with its properties under large sample approximation. In particular, various classes of estimators are identified as particular member of the suggested class. The correct version of the mean squared error of Kadilar and Cingi (2005) class of estimators is derived. It has been shown that the proposed class of estimators is better than Kadilar and Cingi (2005) estimator, usual unbiased estimator, usual combined ratio estimator yRC, combined product estimator yPC, Gangde et al. (1993) type estimator and Searls (1964) type estimator. Numerical illustration is given in support of present study.

Sat Gupta - One of the best experts on this subject based on the ideXlab platform.

  • improved mean estimation of a sensitive variable using auxiliary information in Stratified Sampling
    Journal of Statistics and Management Systems, 2014
    Co-Authors: Rita Sousa, Javid Shabbir, Sat Gupta, Pedro Cortereal
    Abstract:

    AbstractSousa et al. (2010) and Gupta et al. (2012) have recently introduced ratio and regression estimators for the mean of a sensitive variable which perform better than the ordinary mean estimator based on a Randomized Response Technique (RRT). In the present study we extend these estimators to the Stratified Sampling setting.The performance of the proposed estimators is compared to the exiting estimators both theoretically and through a simulation study. We also apply the proposed estimators to some real data.

  • estimating variance of Stratified random sample mean in two phase Sampling using two auxiliary variables
    American Journal of Mathematical and Management Sciences, 2010
    Co-Authors: Sat Gupta, Javid Shabbir
    Abstract:

    SYNOPTIC ABSTRACTIn this paper, we propose a ratio type estimator for estimating the variance of the Stratified sample mean in two phase Sampling using two auxiliary variables. The proposed estimator performs better than the usual unbiased variance estimator, ratio estimator, regression estimator and Walsh (1970) estimator in Stratified Sampling. Two numerical examples are also presented to further illustrate the performance of the proposed estimator.

Abdul Wakeel - One of the best experts on this subject based on the ideXlab platform.

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