A Comparison of Hot Deck Imputation and Substitution Methods in The Estimation of Missing Data

被引：0
|
作者：
Yesilova, Abdullah [1 ]
Kaya, Yilmaz [1 ]
Almali, M. Nuri [2 ]
机构：
[1] Yuzuncu Yil Univ, Fac Agr, Biometry Genet Unit, Van, Turkey
[2] Yuzuncu Yil Univ, Vocat High Sch, Comp Programming, Van, Turkey
来源：
GAZI UNIVERSITY JOURNAL OF SCIENCE | 2011年 / 24卷 / 01期
关键词：
Missing data; Hot Deck imputation; Substitution methods;
D O I：
暂无
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
It is of great importance to obtain data in an accurate and incomplete way for adequate conclusions to be drawn from investigations conducted. Due to various reasons, certain parts of an investigation might not be observed, and as a result of this, data might be missing and obtained incompletely. Missing value may not only be based on a single variable but also a multitude of variables. In this study, missing data in different proportions and belonging to more than a variable were produced. When data were considered within a context which is missing completely at random, Hot Deck imputation, random Hot Deck imputation and substitution methods (mean, median) were compared in the estimation of missing value. As a result of analysis, Hot Deck imputation method was found to be more effective in the estimation of missing value.
引用
收藏
页码：69 / 75
页数：7
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