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Doubly Robust Imputation Using Auxiliary Information
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 Title & Authors
Doubly Robust Imputation Using Auxiliary Information
Park, Hyeon-Ah; Jeon, Jong-Woo; Na, Seong-Ryong;
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 Abstract
Ratio and regression imputations depend on the model of a survey variable and the relation between the survey variable and auxiliary variables. If the model is not true, the unbiasedness of the estimator using the ratio or regression imputation cannot be guaranteed. In this paper, we develop the doubly robust imputation, which satisfies the approximate unbiasedness of the estimator, whether the model assumption is valid or not. The proposed imputation increases the efficiency of estimation by using the population information of the auxiliary variables. The simulation study establishes the theoretical results of this paper.
 Keywords
Imputation;doubly robust;ratio imputation;auxiliary variable;
 Language
Korean
 Cited by
1.
Usage of auxiliary variable and neural network in doubly robust estimation,;;

Journal of the Korean Data and Information Science Society, 2013. vol.24. 3, pp.659-667 crossref(new window)
1.
Usage of auxiliary variable and neural network in doubly robust estimation, Journal of the Korean Data and Information Science Society, 2013, 24, 3, 659  crossref(new windwow)
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