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http://dx.doi.org/10.5351/KJAS.2014.27.7.1229

A Multiple Imputation for Reducing Outlier Effect  

Kim, Man-Gyeom (Department of statistics, Hankuk University of Foreign Studies)
Shin, Key-Il (Department of statistics, Hankuk University of Foreign Studies)
Publication Information
The Korean Journal of Applied Statistics / v.27, no.7, 2014 , pp. 1229-1241 More about this Journal
Abstract
Most of sampling surveys have outliers and non-response missing values simultaneously. In that case, due to the effect of outliers, the result of imputation is not good enough to meet a given precision. To overcome this situation, outlier treatment should be conducted before imputation. In this paper in order for reducing the effect of outlier, we study outlier imputation methods and outlier weight adjustment methods. For the outlier detection, the method suggested by She and Owen (2011) is used. A small simulation study is conducted and for real data analysis, Monthly Labor Statistic and Briquette Consumption Survey Data are used.
Keywords
Outlier detection; outlier imputation; outlier weight adjustment; penalized regression;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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1 Park, D.-I., Kang, H., Han S.-T. and Choi, H. (2013). Comparison study of outlier detection methods in a regression model, Journal of the Korean Data Analysis Society, 15, 177-186.
2 Ren, R. and Chamber, R. L. (2004). Outlier robust imputation of survey data, Proceeding of ASA Section on Survey Research Methods.
3 Rubin, D. B. (1987). Multiple imputation for Nonresponse in Survey, New York.
4 She, Y. and Owen, A. B. (2011). Outlier detection using nonconvex penalized regression, Journal of the American Statistical Association, 106, 626-639.   DOI   ScienceOn
5 Belcher, R (2003). Application of the Hidiroglou-Berthelot method of outlier detection for periodic business surveys, SSC Annual Meeting, Proceeding of the Survey Method Section.
6 Hidiroglou, M. A. and Berthelot, J.-M. (1986). Statistical editing and imputation for Periodic Business Surveys, Survey Methodology, 12, 73-83.
7 Kim, J.-Y. and Shin, K.-I. (2013). Multiple Imputation reducing outlier effect using weight adjustment methods, The Korean Journal of Applied Statistics, 26, 635-647.   과학기술학회마을   DOI
8 Lee, H., Rancourt, E. and Sarndal, C.-E.(1995). Experiment with variance estimation from survey data with imputed value, Journal of Official Statistics, 10, 231-243.
9 Lee, S.-J. and Shin, K.-I. (2008). A Study on the sensitivity of the BLS Methods, Communications of the Korean Statistical Society, 15, No. 6, 843-858.   과학기술학회마을   DOI
10 McCullough, M. and Pennington, T. L. (2009). identifying outliers when creating an imputation based for the Qualterly Financial Report,JSM, Section on Survey Research Methods.