Efficient Imputation Methods to Handle Missing Data in Sample Surveys

被引：0
|
作者：
Singh, G. N. [1 ]
Jaiswal, Ashok K. [1 ]
机构：
[1] Indian Sch Mines, Indian Inst Technol, Dept Math & Comp, Dhanbad 826004, Bihar, India
来源：
JOURNAL OF STATISTICAL THEORY AND PRACTICE | 2022年 / 16卷 / 03期
关键词：
Missing data; Mean square error; Imputation method; Population mean; Percent relative efficiency (PRE); RATIO METHOD; ESTIMATORS;
D O I：
10.1007/s42519-022-00266-8
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
This paper develops a class of modified difference-cum-exponential type imputation methods and corresponding point estimators to estimate the finite population mean in case of missing data problem. We have shown that the proposed strategies use the available auxiliary information effectively and give better results in comparison to some of the existing estimators. The performance of the proposed procedures over others is supplemented by the Monte Carlo simulation technique and presented through tables and graphs. Suitable recommendations are made to survey researchers.
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收藏
页数：28
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