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In human surveys, people are asked highly confidential questions concerning a sensitive variable. This article concentrate on the estimation of population mean of sensitive variable under two phase sampling using ORRT models. Also, the presence of non response and measurement errors is of concern while discussing the properties of the proposed estimators. The conditions under which the proposed estimator perform relatively better than the estimators based on recent studies are obtained. Simulation study also carried out in different situations over the data set of natural population and fictitious population to support the theoretical findings.

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In the context of a sample survey, the collection of information on a sensitive variable is difficult, which may cause nonresponse and measurement errors. Due to this, the estimates can be biased and the variation may increase. To overcome this difficulty, we propose an estimator for the estimation of a sensitive variable by using auxiliary information in the presence of nonresponse and measurement errors simultaneously. The properties of the proposed estimators have been studied, and the results have been compared with those of the usual complete response estimator. Theoretical results have been verified through a simulation study using an artificial population and two real-life applications. With the outcomes of the proposed estimator, a suitable recommendation has been made to the survey statisticians for their real-life application.

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