A response probability estimation for non-ignorable non-response

被引:3
|
作者
Chung, Hee Young [1 ]
Shin, Key-Il [1 ]
机构
[1] Hankuk Univ Foreign Studies, Dept Stat, 81 Oedae Ro, Yongin 17035, Gyeonggido, South Korea
基金
新加坡国家研究基金会;
关键词
response probability model; bias estimation; sample distribution; population distribution; post-stratification; ADJUST;
D O I
10.29220/CSAM.2022.29.2.263
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
Use of appropriate technique for non-response occurring in sample survey improves the accuracy of the estimation. Many studies have been conducted for handling non-ignorable non-response and commonly the response probability is estimated using the propensity score method. Recently, post-stratification method to obtain the response probability proposed by Chung and Shin (2017) reduces the effect of bias and gives a good performance in terms of the MSE. In this study, we propose a new response probability estimation method by combining the propensity score adjustment method using the logistic regression model with post-stratification method used in Chung and Shin (2017). The superiority of the proposed method is confirmed through simulation.
引用
收藏
页码:263 / 275
页数:13
相关论文
共 50 条
  • [41] Modelling non-ignorable missing-data mechanisms with item response theory models
    Holman, R
    Glas, CAW
    BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY, 2005, 58 : 1 - 17
  • [42] Very serious and non-ignorable problem: Crisis in emergency medical response in catastrophic event
    Shen, Weifeng
    Jiang, Libing
    Zhang, Mao
    Ma, Yuefeng
    Jiang, Guanyu
    He, Xiaojun
    EMERGENCY MEDICINE AUSTRALASIA, 2015, 27 (06) : 573 - 579
  • [43] Indices of non-ignorable selection bias for proportions estimated from non-probability samples
    Andridge, Rebecca R.
    West, Brady T.
    Little, Roderick J. A.
    Boonstra, Philip S.
    Alvarado-Leiton, Fernanda
    JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 2019, 68 (05) : 1465 - 1483
  • [44] Non-ignorable missingness in logistic regression
    Wang, Joanna J. J.
    Bartlett, Mark
    Ryan, Louise
    STATISTICS IN MEDICINE, 2017, 36 (19) : 3005 - 3021
  • [45] A SIMPLE AND EFFICIENT ESTIMATION METHOD FOR MODELS WITH NON-IGNORABLE MISSING DATA
    Ai, Chunrong
    Linton, Oliver
    Zhang, Zheng
    STATISTICA SINICA, 2020, 30 (04) : 1949 - 1970
  • [46] Non-response in probability sample surveys in the Czech Republic
    Krejci, Jindrich
    SOCIOLOGICKY CASOPIS-CZECH SOCIOLOGICAL REVIEW, 2007, 43 (03): : 561 - 587
  • [47] VARIANCE ESTIMATION IN PRESENCE OF RANDOM NON-RESPONSE
    Kumar, Sunil
    JOURNAL OF RELIABILITY AND STATISTICAL STUDIES, 2014, 7 (02): : 65 - 70
  • [48] Robust estimation of distribution functions and quantiles with non-ignorable missing data
    Zhao, Pu-Ying
    Tang, Man-Lai
    Tang, Nian-Sheng
    CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 2013, 41 (04): : 575 - 595
  • [49] Estimation of non-response bias in the Medicare FFSHOS
    McCall, N
    Khatutsky, G
    Smith, K
    Pope, GC
    HEALTH CARE FINANCING REVIEW, 2004, 25 (04): : 27 - 41
  • [50] Estimation of mean vector in presence of non-response
    Tripathi, TP
    Khare, BB
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 1997, 26 (09) : 2255 - 2269