Some Logarithmic And Sine-Type Imputation Techniques For Missing Data In Survey Sampling In The Presence Of Measurement Errors

One of the main sources of non-sampling errors is missing data due to non-response. Various methods are adopted to deal with this problem, one of which is the method of imputation. In this paper, a few logarithmic and sine type imputation techniques have been proposed for estimating the population mean and the effect of measurement errors on the resultant estimators has been examined. Their properties in terms of bias and mean square errors have been studied. Empirical studies have been carried out on real and simulated data sets to show the efficiency of the proposed estimators over contemporary estimators. Suitable recommendations have been put forward to the survey statisticians for applications in real-life problems.