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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.
  • 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 en 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.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Modelos Estadísticos Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Modelos Estadísticos Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Idioma: En Año: 2022 Tipo del documento: Article