Document Detail


Time-varying coefficient proportional hazards model with missing covariates.
MedLine Citation:
PMID:  23044762     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Missing covariates often arise in biomedical studies with survival outcomes. Existing approaches for missing covariates generally assume proportional hazards. The proportionality assumption may not hold in practice, as illustrated by data from a mouse leukemia study with covariate effects changing over time. To tackle this restriction, we study the missing data problem under the varying-coefficient proportional hazards model. On the basis of the local partial likelihood approach, we develop inverse selection probability weighted estimators. We consider reweighting and augmentation techniques for possible improvement of efficiency and robustness. The proposed estimators are assessed via simulation studies and illustrated by application to the mouse leukemia data.
Authors:
Xiao Song; Ching-Yun Wang
Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S.     Date:  2012-10-09
Journal Detail:
Title:  Statistics in medicine     Volume:  32     ISSN:  1097-0258     ISO Abbreviation:  Stat Med     Publication Date:  2013 May 
Date Detail:
Created Date:  2013-05-08     Completed Date:  2014-01-02     Revised Date:  2014-06-02    
Medline Journal Info:
Nlm Unique ID:  8215016     Medline TA:  Stat Med     Country:  England    
Other Details:
Languages:  eng     Pagination:  2013-30     Citation Subset:  IM    
Copyright Information:
Copyright © 2012 John Wiley & Sons, Ltd.
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MeSH Terms
Descriptor/Qualifier:
Animals
Computer Simulation
Leukemia / genetics,  virology
Likelihood Functions*
Mice
Proportional Hazards Models*
Survival Analysis
Grant Support
ID/Acronym/Agency:
CA53996/CA/NCI NIH HHS; P01 CA053996/CA/NCI NIH HHS; R01 ES017030/ES/NIEHS NIH HHS; R01ES017030/ES/NIEHS NIH HHS
Comments/Corrections

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