Some Imputation Methods to Minimize the Effect of Non Response in Two-Occasion Rotation Patterns

Abstract

Among modern strategies applied to cope with non response, a major problem faced by survey statisticians, imputation is one of the most common. Imputation is the filling up method of incomplete data for adapting the standard analytic model in statistics. The purpose of the present work is to study the use of imputation methods in dealing with non response which occur at both occasions in two-occasion successive (rotation) sampling. Chain-type regressions in ratio estimators have been proposed for estimating the population mean at current occasion. Expressions for optimum estimator and its mean square error have been derived. To study the effectiveness of the imputation methods, performances of the proposed estimators are compared in two different situations: with and without non response. Behavior of the proposed estimators is demonstrated through empirical studies.

Keywords:

• Chain-type regression in ratio
• Imputation
• Missing data
• Non response
• Optimum replacement policy
• Successive sampling

Mathematics Subject Classification:

• 62D05

Acknowledgments

The authors are thankful to the honorable referee for his valuable and inspiring suggestions. The authors are also thankful to the University Grants Commission, New Delhi for providing the financial assistance to carry out the present work.

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