Semiparametric regression models for repeated measures of mortal cohorts with non-monotone missing outcomes and time-dependent covariates

被引：12

作者：

Shardell, Michelle ^{[1
]}

Hicks, Gregory E. ^{[2
]}

Miller, Ram R. ^{[1
]}

Magaziner, Jay ^{[1
]}

机构：

[1] Univ Maryland, Dept Epidemiol & Prevent Med, Baltimore, MD 21201 USA

[2] Univ Delaware, Dept Phys Therapy, Newark, DE USA

来源：

STATISTICS IN MEDICINE | 2010年 / 29卷 / 22期

基金：

美国国家卫生研究院;

关键词：

gerontology; longitudinal data; missing data; missing not at random; sensitivity analysis; LONGITUDINAL BINARY DATA; LOWER-EXTREMITY FUNCTION; HIP FRACTURE; SENSITIVITY-ANALYSIS; ESTIMATING EQUATION; DROP-OUT; NONRESPONSE; DEATH; INTERLEUKIN-6; INFERENCE;

D O I：

10.1002/sim.3985

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

We propose a semiparametric marginal modeling approach for longitudinal analysis of cohorts with data missing due to death and non-response to estimate regression parameters interpreted as conditioned on being alive. Our proposed method accommodates outcomes and time-dependent covariates that are missing not at random with non-monotone missingness patterns via inverse-probability weighting. Missing covariates are replaced by consistent estimates derived from a simultaneously solved inverse-probability-weighted estimating equation. Thus, we utilize data points with the observed outcomes and missing covariates beyond the estimated weights while avoiding numerical methods to integrate over missing covariates. The approach is applied to a cohort of elderly female hip fracture patients to estimate the prevalence of walking disability over time as a function of body composition, inflammation, and age. Copyright (C) 2010 John Wiley & Sons, Ltd.

引用

页码：2282 / 2296

页数：15

共 20 条

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[13] Asymptotic Theory for Relative-Risk Models with Missing Time-Dependent Covariates
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[J]. Acta Mathematicae Applicatae Sinica, English Series, 2018, 34 : 669 - 692
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