期刊论文详细信息
JOURNAL OF MULTIVARIATE ANALYSIS 卷:123
Model assisted Cox regression
Article
Mondal, Shoubhik1  Subramanian, Sundarraman1 
[1] New Jersey Inst Technol, Dept Math Sci, Ctr Appl Math & Stat, Newark, NJ 07102 USA
关键词: Empirical coverage;    Event-time hazard;    Gaussian process;    Loewner ordering;    Mean integrated squared error;    Missing at random;   
DOI  :  10.1016/j.jmva.2013.09.013
来源: Elsevier
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【 摘 要 】

Semiparametric random censorship (SRC) models (Dikta, 1998) [7], derive their rationale from their ability to utilize parametric ideas within the random censorship environment. An extension of this approach is developed for Cox regression, producing new estimators of the regression parameter and baseline cumulative hazard function. Under correct parametric specification, the proposed estimator of the regression parameter and the baseline cumulative hazard function are shown to be asymptotically as or more efficient than their standard Cox regression counterparts. Numerical studies are presented to showcase the efficacy of the proposed approach even under significant misspecification. Two real examples are provided. A further extension to the case of missing censoring indicators is also developed and an illustration with pseudo-real data is provided. (C) 2013 Elsevier Inc. All rights reserved.

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