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A generalized class of estimators for sensitive variable in the presence of measurement error and non-response.
Zahid, Erum; Shabbir, Javid; Gupta, Sat; Onyango, Ronald; Saeed, Sadia.
Affiliation
  • Zahid E; Department of Applied Mathematics & Statistics, Institute of Space Technology, Islamabad, Pakistan.
  • Shabbir J; Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan.
  • Gupta S; Department of Mathematics & Statistics, University of North Carolina at Greensboro, Greensboro, NC, United States of America.
  • Onyango R; Department of Applied Statistical, Financial Mathematics and Actuarial Science Jaramogi Oginga Odinga University of Science and Technology, Bondo, Kenya.
  • Saeed S; Department of Applied Mathematics & Statistics, Institute of Space Technology, Islamabad, Pakistan.
PLoS One ; 17(1): e0261561, 2022.
Article in En | MEDLINE | ID: mdl-35045076
ABSTRACT
In this paper, a general class of estimators is proposed for estimating the finite population mean for sensitive variable, in the presence of measurement error and non-response in simple random sampling. Expressions for bias and mean square error up to first order of approximation, are derived. Impact of measurement errors is examined using real data sets, including the survey conducted at Quaid-i-Azam University, Islamabad. Simulated data sets are also used to observe the performance of the proposed estimators in comparison to some other estimators. We obtain the empirical bias and MSE values for the proposed and the competing estimators.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Models, Statistical Type of study: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2022 Document type: Article Affiliation country: Pakistan

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Models, Statistical Type of study: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2022 Document type: Article Affiliation country: Pakistan