An enhanced ratio-cum-product estimator with non-response and observational error by utilizing ORRT models: a sensitive estimation approach

Abstract

The notion of ratio-cum-product estimator was implemented in this work to estimate the population means of sensitive study variables in the existence of non-response and measurement error simultaneously under simple random sampling and two-phase sampling by employing ORRT models. The specifications (bias and MSE's) of the proposed and obtained estimators were derived up to the second-order approximation by using two auxiliary variable(s). The efficiency requirements of the suggested estimators explored in the study are provided. An operational study is analysed to ascertain the effectiveness of these estimators leveraging stimulated data sets. Ultimately, the findings revealed that the proposed ratio-cum-product estimators have the lowest mean squared error amongst all class of estimators in simple random sampling and two-phase sampling.