Author(s): Naveen GP and Manoj Kumar

Abstract: The analysis of data is complicated when two or more values are missing. Missing data generates bias and makes it more difficult to handle and analysis of data, which reduces efficiency. Imputation is a method where by imputed values are used to fill the missing values based on the data that is already existed and available axillary information. There are various techniques available to impute the values. After imputing the missing observations, we obtained a complete data set that can be analysed using some traditional methods. Previously imputation procedures like Mean method of Imputation, Ratio method of imputation, compromised method of imputation procedures are used in order to impute the missing observations. In this study an alternate estimator of population mean using estimator given by Singh et al. (2016) under compromised imputation method is given. The expression for bias and mean squared error (MSE) up to the first order approximation are derived. An numerical study is also carried out in order to compare the efficiency of the estimator with the previously existing estimators.

Pages: 27-33 | Views: 59 | Downloads: 12

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