Abstract
This article presents an efficient variant of the usual product and ratio methods of estimation of population mean of a study variable Y in the context of simple random sampling when the observations of both study variable and auxiliary variable are supposed to be commingled with measurement error. The bias and mean squared error of proposed class of estimators have been derived and studied under measurement error. Monte Carlo simulation and numerical studies have been carried out to study the properties of the estimators and compared with mean square error and percentage relative efficiency of the estimator when variables are free from measurement errors.
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