Abstract

In this scripture, we ponder the problem of efficient estimation of population mean of study variable utilizing information on highly correlated auxiliary variables under the presence of non-response on either of the variables. For this purpose, we suggest, an improved estimator under three different situations of non-response. Under the first situation, estimation of population mean is done with the problem of non-response on both the study and the auxiliary variables with the additional condition that the population means of the auxiliary variables are known. The second situation is to estimate the population mean of primary variable when the problem of non-response is only on the primary variable but the population means of the auxiliary variables are known while under the third situation estimation is performed with the problem of non-response on both the study and the auxiliary variables but population mean of one of the auxiliary variables is unknown. We study the sampling properties of the suggested estimator under above three different situations of non-response. We compare the proposed estimator with the competing estimators of population mean, under three different situations of non-response. The efficiency conditions are obtained for all three situations. A numerical study is also carried out to verify the efficiency conditions.

Highlights

  • In mail questionnaire the problem of non-response is observed at a very large rate and the unknown bias could be a big factor in such situations

  • We suggest a new estimator of population mean of study variable using known information on the auxiliary variables under the presence of non-response error

  • 3.5 Suggested Estimator under the Second Strategy Motivated by Sharma and Pal (2018); Searls (1964), we suggest the following exponential ratiocum-product estimator of population mean of the primary variable, utilizing known information on both the positively and negatively correlated auxiliary variables as, t *(2) RPe

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Summary

Introduction

Sampling is inevitable whenever the population is large because of the time and money constraints. Tabasum and Khan (2006); Singh et al (2010) suggested improved estimation of finite population mean under non response error in two-phase or double sampling scheme. Shabbir and Nasir (2013) studied estimating the finite population mean using two auxiliary variables in two phase sampling in the presence of non response. Yadav et al (2018) studied the estimation of finite population mean using known coefficient of variation in the simultaneous presence of non-response and measurement errors under double sampling scheme. Sud and Srivastva (2000); Srivastava and Shalabh (2001) suggested improved ratio and regression type estimators of population mean under the problem of measurement errors respectively in survey sampling. We suggest a new estimator of population mean of study variable using known information on the auxiliary variables under the presence of non-response error.

Suggested Estimator under the First Strategy
Review of Existing Estimators under the Second Strategy
Suggested Estimator under the Second Strategy Motivated by Sharma and
Review of Existing Estimators under the Third Strategy
Suggested Estimator under the Third Strategy Motivated by Sharma and
Comparison with Competing Estimators under Third Strategy of Non-Response
Results and Discussion
Conclusion
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