The crux of this study is to propose some modified and improved compromised imputation
methods and their corresponding point estimators to estimate the population mean using …

In real-life scenarios, encountering data with missing values is common, and if not managed
carefully from the outset of a study, it can lead to significant biases in survey estimates …

Sample surveys are often affected by missing observations and non-response caused by
therespondents' refusal or unwillingness to provide the requested information or due to …

This paper introduces a difference-type exponential imputation method and the
corresponding point estimators. Bias and mean-squared error of the proposed estimators …

In this paper, a class of population mean estimators is suggested in the presence of missing
data in a study variable by transforming an auxiliary variable under simple random sampling …

We discuss the problem of non-response in the study of auxiliary variables while estimating
population mean in stratified random sampling. We propose a class of exponential-type …

In this paper, we investigate the issue of non-response in two different instances for
estimating the population mean in stratified random sampling. Case I occurs when non …

This article deals with estimation of population mean for missing data in simple random
sampling. The properties of the proposed procedure are studied up-to first order of …

The present article offers more efficient imputation based estimators of the population mean
under the framework of two-phase sampling in presence of an auxiliary variable. The …

Present paper propose a generalized class of imputation strategy for estimating population
mean under the framework of two-phase sampling design by using auxiliary information and …