Optimal imputation of missing data for estimation of population mean

被引：28

作者：

Bhushan, Shashi ^{[1
]}

Pandey, Abhay Pratap ^{[2
]}

机构：

[1] Dr Shakuntala Misra Natl Rehabil Univ, Dept Math & Stat, Lucknow 226017, Uttar Pradesh, India

[2] Babasaheb Bhimrao Ambedkar Univ, Dept Appl Stat, Lucknow 226025, Uttar Pradesh, India

来源：

JOURNAL OF STATISTICS & MANAGEMENT SYSTEMS | 2016年 / 19卷 / 06期

关键词：

Missing data; Imputation; Searls-type estimators;

D O I：

10.1080/09720510.2016.1220099

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：

In this article, we have addressed the issue of optimality under imputation by using Searls (1964) idea. We have proposed three new Searls-type difference (STD) methods for imputation of missing data. The resultant STD estimators are better than the estimators proposed by Kadilar and Cingi (2008) and Diana and Perri (2010). An analytical comparison shows that the proposed optimal methods are always better that the respective regression methods of imputation. Theoretical results are supported by an empirical study.

引用

页码：755 / 766

页数：12

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