Cox Regression with Covariates Missing Not at Random

被引：8

作者：

Cook V.J. ^{[1
]}

Hu X.J. ^{[2
]}

Swartz T.B. ^{[2
]}

机构：

[1] BC Centre for Disease Control, University of British Columbia, Vancouver, British Columbia V5Z 4R4

[2] Department of Statistics and Acturial Sciences, Simon Fraser University, Burnaby

来源：

Statistics in Biosciences | 2011年 / 3卷 / 2期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Event time; Missing data; Semiparametric estimation; Sensitivity analysis; Supplementary information;

D O I：

10.1007/s12561-010-9031-0

中图分类号：

学科分类号：

摘要：

This paper considers estimation under the Cox proportional hazards model with right-censored event times in the presence of covariates missing not at random (MNAR). We propose an approach derived from likelihood estimation utilizing supplementary information. We show that available additional information not only helps to account appropriately for the missing covariates but also leads to estimation procedures which are natural and easy to implement. A medical example is used throughout the paper to motivate the problem and to illustrate the proposed methodology. © 2010 International Chinese Statistical Association.

引用

页码：208 / 222

页数：14

共 50 条

[21] Recalibration based on an approximate relative risk estimator in Cox regression with missing covariates
Wang, CY
Xie, SX
Prentice, RL
[J]. STATISTICA SINICA, 2001, 11 (04) : 1081 - 1104
[22] Double-semi parametric method for missing covariates in cox regression models
Chen, HY
[J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2002, 97 (458) : 565 - 576
[23] Nonparametric regression with responses missing at random and the scale depending on auxiliary covariates
Jiang, Tian
[J]. JOURNAL OF NONPARAMETRIC STATISTICS, 2023, 35 (02) : 302 - 322
[24] Estimation and test procedures for composite quantile regression with covariates missing at random
Ning, Zijun
Tang, Linjun
[J]. STATISTICS & PROBABILITY LETTERS, 2014, 95 : 15 - 25
[25] Sieve maximum likelihood estimation for regression models with covariates missing at random
Chen, Qingxia
Zeng, Donglin
Ibrahim, Joseph G.
[J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2007, 102 (480) : 1309 - 1317
[26] Robust location estimators in regression models with covariates and responses missing at random
Bianco, Ana M.
Boente, Graciela
Gonzalez-Manteiga, Wenceslao
Perez-Gonzalez, Ana
[J]. JOURNAL OF NONPARAMETRIC STATISTICS, 2020, 32 (04) : 915 - 939
[27] A comparison of multiple imputation and fully augmented weighted estimators for Cox regression with missing covariates
Qi, Lihong
Wang, Ying-Fang
He, Yulei
[J]. STATISTICS IN MEDICINE, 2010, 29 (25) : 2592 - 2604
[28] Estimation in the Cox cure model with covariates missing not at random, with application to disease screening/prediction
Guo, Lisha
Xiong, Yi
Hu, X.
[J]. CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 2020, 48 (04): : 608 - 632
[29] Cox regression with dependent error in covariates
Huang, Yijian
Wang, Ching-Yun
[J]. BIOMETRICS, 2018, 74 (01) : 118 - 126
[30] Weighted composite quantile regression for single index model with missing covariates at random
Huilan Liu
Hu Yang
Changgen Peng
[J]. Computational Statistics, 2019, 34 : 1711 - 1740

← 1 2 3 4 5 →