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http://dx.doi.org/10.5351/KJAS.2006.19.1.057

Missing Imputation Methods Using the Spatial Variable in Sample Survey  

Lee Jin-Hee (Cancer Registration Branch, Research Institute for National Cancer and Evaluation, National Cancer Center)
Kim Jin (Regional Statistics and Sampling Division, Korea National Statistical Office)
Lee Kee-Jae (Department of Information Statistics, Korea National Open University)
Publication Information
The Korean Journal of Applied Statistics / v.19, no.1, 2006 , pp. 57-67 More about this Journal
Abstract
In sampling survey, nonresponse tend to occur inevitably. If we use information from respondents only, the estimates will be baised. To overcome this, various non-response imputation methods have been studied. If there are few auxiliary variables for replacing missing imputation or spatial autocorrelation exists between respondents and nonrespondents, spatial autocorrelation can be used for missing imputation. In this paper, we apply several nonresponse imputation methods including spatial imputation for the analysis of farm household economy data of the Gangwon-Do in 2002 as an example. We show that spatial imputation is more efficient than other methods through the numerical simulations.
Keywords
Missing data; Spatial autocorrelation; SAR model; Nearest neighborhood; Spatial imputation;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
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