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H. J. Chang and K. C. Huang, “Ratio Estimation in Survey Sampling When Some Observations Are Missing,” Information and Management Sciences, Vol. 12, No. 2, 2001, pp. 1-9.
http://dx.doi.org/10.1016/S0378-7206(01)00075-1

has been cited by the following article:

• TITLE: Exponential Ratio Type Estimators of Population Mean under Non-Response

  AUTHORS: Lovleen Kumar Grover, Parmdeep Kaur

  KEYWORDS: Auxiliary Variable; Bias; Mean Square Error; Non-Response; Simple Random Sampling without Replacement; Study Variable

  JOURNAL NAME: Open Journal of Statistics, Vol.4 No.1, February 26, 2014

  ABSTRACT: This paper proposes some exponential ratio type estimators of population mean under the situations when certain observations for some sampling units are missing. These missing observations may be for either auxiliary variable or study variable. The biases and mean square errors of the proposed estimators have been derived, up to the first order of approximation. The proposed estimators are compared theoretically with that of the existing ratio type estimators defined by [1]. It has been found that the proposed exponential ratio type estimators perform better than the mean per unit estimator even for the low positive correlation between study variable and auxiliary variable. Moreover, we obtained the conditions for which our proposed estimators are better than the corresponding ratio type estimators of [1]. To verify the theoretical results obtained, a simulation study is carried out finally.