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Weight Reduction Method for Outlier in Survey Sampling
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 Title & Authors
Weight Reduction Method for Outlier in Survey Sampling
Kim Jin;
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 Abstract
Outliers in survey are a perennial problem for applied survey statisticians to estimate the total or mean of population. The influence of outliers is more increasing as they have large weights in survey sampling. Many techniques have been studied to lower the impact of outliers on sample survey estimates. Outliers can be downweighted by winsorization or reducing the weight of outliers. The weight reduction is more reasonable than replacing one outlier by one value of non-outliers, because it has at least one unit. In this paper, we suggest the square root transformation of weight as the weight reduction method. We show this method is efficient with real data, and it's also easy to apply in practical affairs.
 Keywords
Outliers;Winsorization;Weight reduction;Transformation;
 Language
Korean
 Cited by
1.
가중치 보정을 이용한 다중대체법,김진영;신기일;

응용통계연구, 2013. vol.26. 4, pp.635-647 crossref(new window)
1.
Multiple Imputation Reducing Outlier Effect using Weight Adjustment Methods, Korean Journal of Applied Statistics, 2013, 26, 4, 635  crossref(new windwow)
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