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
相关论文
共 50 条
  • [31] Efficient estimation with missing data and endogeneity
    Rai, Bhavna
    ECONOMETRIC REVIEWS, 2023, 42 (02) : 220 - 239
  • [32] New Chain Imputation Methods for Estimating Population Mean in the Presence of Missing Data Using Two Auxiliary Variables
    Bhushan, Shashi
    Pandey, Abhay Pratap
    COMMUNICATIONS IN MATHEMATICS AND STATISTICS, 2023, 11 (02) : 325 - 340
  • [33] Testing Measurement Invariance with Ordinal Missing Data: A Comparison of Estimators and Missing Data Techniques
    Chen, Po-Yi
    Wu, Wei
    Garnier-Villarreal, Mauricio
    Kite, Benjamin Arthur
    Jia, Fan
    MULTIVARIATE BEHAVIORAL RESEARCH, 2020, 55 (01) : 87 - 101
  • [34] New Chain Imputation Methods for Estimating Population Mean in the Presence of Missing Data Using Two Auxiliary Variables
    Shashi Bhushan
    Abhay Pratap Pandey
    Communications in Mathematics and Statistics, 2023, 11 : 325 - 340
  • [35] Caution in the interpretation of association in presence of missing data
    Croiseau, P
    Clerget-Darpoux, F
    Babron, MC
    Génin, E
    ANNALS OF HUMAN GENETICS, 2005, 69 : 766 - 766
  • [36] Flexible variable selection in the presence of missing data
    Williamson, Brian D.
    Huang, Ying
    INTERNATIONAL JOURNAL OF BIOSTATISTICS, 2024, 20 (02) : 347 - 359
  • [37] A comparison of doubly robust estimators of the mean with missing data
    Yang, Ye
    Little, Roderick
    JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2015, 85 (16) : 3383 - 3403
  • [38] Testing for multivariate outliers in the presence of missing data
    Woodward, WA
    Sain, SR
    Grah, HL
    Zhao, BJ
    Fisk, MD
    PURE AND APPLIED GEOPHYSICS, 2002, 159 (04) : 889 - 903
  • [39] Estimating population proportions in the presence of missing data
    Alvarez, E.
    Arcos, A.
    Gonzalez, S.
    Munoz, J. F.
    Rueda, M.
    JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2013, 237 (01) : 470 - 476
  • [40] Estimation of causal effects in clinical endpoint bioequivalence studies in the presence of intercurrent events: noncompliance and missing data
    Lou, Yiyue
    Jones, Michael P.
    Sun, Wanjie
    JOURNAL OF BIOPHARMACEUTICAL STATISTICS, 2019, 29 (01) : 151 - 173
12345