Mean estimation with calibration techniques in presence of missing data

被引：14
|
作者：
Rueda, M.
Martinez, S.
Martinez, H.
Arcos, A.
机构：
[1] Univ Granada, Dept Stat & Operat Res, E-18071 Granada, Spain
[2] Univ Almeria, Dept Appl Math & Stat, Almeria, Spain
[3] Univ Murcia, Dept Stat & Operat Res, E-30001 Murcia, Spain
来源：
COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2006年 / 50卷 / 11期
关键词：
calibration estimators; missing data; Horvitz-Thompson estimator;
D O I：
10.1016/j.csda.2005.06.003
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The problem of estimating the population mean using calibration estimators when some observations on the study and auxiliary characteristics are missing from the sample, is considered. Some new classes of estimators are proposed for any sampling design. These new classes employ to all observation (incomplete cases too) in the estimation without using any imputation techniques. On the basis of properties derived and some simulation results, the proposed estimators are compared with other complete case estimators. (C) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码：3263 / 3277
页数：15
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