Use of generalized randomized response model for enhancement of finite population variance: A simulation approach.

Gupta et al. suggested an improved estimator by using the Diana and Perri model in estimating the finite population variance using the single auxiliary variable. On the same lines, Saleem et al. proposed a new scrambled randomized response model (RRT) based on two auxiliary variables for estimating...

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Main Authors: Javid Shabbir, Zabihullah Movaheedi
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2024-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0315658
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author Javid Shabbir
Zabihullah Movaheedi
author_facet Javid Shabbir
Zabihullah Movaheedi
author_sort Javid Shabbir
collection DOAJ
description Gupta et al. suggested an improved estimator by using the Diana and Perri model in estimating the finite population variance using the single auxiliary variable. On the same lines, Saleem et al. proposed a new scrambled randomized response model (RRT) based on two auxiliary variables for estimating the finite population variance. Recently Azeem et al. presented a new randomized response model in estimating the finite population variance. It is observed that Bias and MSE of these estimators up to first order of approximation seem to lack sufficient information. In this study, we rectify the bias and MSE expressions of the estimators proposed by Gupta et al., Saleem et al. and Azeem et al. Additionally, we suggest a new generalized class of estimators that is more efficient in comparison to the previously considered estimators. A simulation study is conducted to establish the behavior of the estimators. The suggested estimator performs better than the estimators considered by the authors earlier.
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publishDate 2024-01-01
publisher Public Library of Science (PLoS)
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spelling doaj-art-d5ff752dfe2342c2acc60dc646ea8afa2025-08-20T02:35:15ZengPublic Library of Science (PLoS)PLoS ONE1932-62032024-01-011912e031565810.1371/journal.pone.0315658Use of generalized randomized response model for enhancement of finite population variance: A simulation approach.Javid ShabbirZabihullah MovaheediGupta et al. suggested an improved estimator by using the Diana and Perri model in estimating the finite population variance using the single auxiliary variable. On the same lines, Saleem et al. proposed a new scrambled randomized response model (RRT) based on two auxiliary variables for estimating the finite population variance. Recently Azeem et al. presented a new randomized response model in estimating the finite population variance. It is observed that Bias and MSE of these estimators up to first order of approximation seem to lack sufficient information. In this study, we rectify the bias and MSE expressions of the estimators proposed by Gupta et al., Saleem et al. and Azeem et al. Additionally, we suggest a new generalized class of estimators that is more efficient in comparison to the previously considered estimators. A simulation study is conducted to establish the behavior of the estimators. The suggested estimator performs better than the estimators considered by the authors earlier.https://doi.org/10.1371/journal.pone.0315658
spellingShingle Javid Shabbir
Zabihullah Movaheedi
Use of generalized randomized response model for enhancement of finite population variance: A simulation approach.
PLoS ONE
title Use of generalized randomized response model for enhancement of finite population variance: A simulation approach.
title_full Use of generalized randomized response model for enhancement of finite population variance: A simulation approach.
title_fullStr Use of generalized randomized response model for enhancement of finite population variance: A simulation approach.
title_full_unstemmed Use of generalized randomized response model for enhancement of finite population variance: A simulation approach.
title_short Use of generalized randomized response model for enhancement of finite population variance: A simulation approach.
title_sort use of generalized randomized response model for enhancement of finite population variance a simulation approach
url https://doi.org/10.1371/journal.pone.0315658
work_keys_str_mv AT javidshabbir useofgeneralizedrandomizedresponsemodelforenhancementoffinitepopulationvarianceasimulationapproach
AT zabihullahmovaheedi useofgeneralizedrandomizedresponsemodelforenhancementoffinitepopulationvarianceasimulationapproach