Formulation of logarithmic type estimators to estimate population mean in successive sampling in presence of random non response and measurement errors

Abstract

This paper considers the problem of estimation of population mean of the study character in two-occasion successive sampling in presence of non-response and measurement error. A logarithmic type imputation technique has been developed to reduce the nuisance effect of non-response in sample surveys. Utilizing information available on a highly positively or highly negatively correlated auxiliary variable, a logarithmic type estimator is proposed and its properties, including bias and mean square error, are discussed. An optimal replacement policy has been derived, and effect of measurement errors on the mean square error of the estimator has been studied. Empirical studies have been carried out using both real and simulated data, and suitable recommendations have been put forward to the survey statisticians for applications in real life problems.

Keywords:

• Two-occasion successive sampling
• Random non-response
• Imputation
• Auxiliary variable
• Bias
• Mean square error
• Measurement error
• Simulation study

Acknowledgments

We are thankful to IIT (ISM) Dhanbad for providing the infrastructure facilities. We would also like to thank the honorable reviewer for his expert opinion and valuable suggestions that helped to bring this paper to its current form.

Additional information

Funding

Department of Science and Technology, Science & Engineering Research Board (DST-SERB), Government of India, Grant Number EMR/2017/000882.