A composite class of estimators to deal with the issue of variance estimation under the situations of random non-response in two-occasion successive sampling

Abstract

Missing data often creates complications in data analysis for any type of scientific investigations. The non response is the source of missing data and it is an unavoidable phenomenon in survey sampling. This problem becomes more severe in the case of repeated surveys because of its repetitious nature. The missing data due to random causes which we call as random non-response is an important issue which needs to be dealt with a more cautious approach. To address these thoughts, this study is an attempt to reduce the adverse impact of random non response in the estimation of population variance on the current occasion in two-occasion successive sampling. A composite class of estimators for estimation of population variance on the current occasion has been proposed and its properties are deeply examined. An empirical study is carried out to show the efficacious performances of the proposed class of estimators over an estimator defined for the complete response situation. Suitable recommendations are made to the survey practitioners for their real-life practical applications.

KEYWORDS:

• Successive sampling
• Missing data
• Variance estimations
• Auxiliary variable
• Bias
• Mean square error

Mathematics subject classification:

• 62D05

Acknowledgments

Authors are thankful to the IIT(ISM), Dhanbad, for providing the financial assistance and necessary infrastructure to carry out the present research work.