| Time-varying coefficient proportional hazards model with missing covariates. | |
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MedLine Citation:
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PMID: 23044762 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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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. Copyright © 2012 John Wiley & Sons, Ltd. |
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Authors:
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Xiao Song; Ching-Yun Wang |
Publication Detail:
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Type: JOURNAL ARTICLE Date: 2012-10-9 |
Journal Detail:
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Title: Statistics in medicine Volume: - ISSN: 1097-0258 ISO Abbreviation: Stat Med Publication Date: 2012 Oct |
Date Detail:
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Created Date: 2012-10-9 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 8215016 Medline TA: Stat Med Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Copyright Information:
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Copyright © 2012 John Wiley & Sons, Ltd. |
Affiliation:
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Department of Epidemiology and Biostatistics, University of Georgia, Athens, GA, U.S.A. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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