Document Detail

A semiparametric marginal mixture cure model for clustered survival data.
MedLine Citation:
PMID:  23203908     Owner:  NLM     Status:  Publisher    
We consider a marginal model for the regression analysis of clustered failure time data with a cure fraction. We propose to use novel generalized estimating equations in an expectation-maximization algorithm to estimate regression parameters in a semiparametric proportional hazards mixture cure model. The dependence among the cure statuses and among the survival times of uncured patients within clusters are modeled by working correlation matrices in the estimating equations. We use a bootstrap method to obtain the variances of the estimates. We report a simulation study to demonstrate a substantial efficiency gain of the proposed method over an existing marginal method. Finally, we apply the model and the proposed method to a set of data from a multi-institutional study of tonsil cancer patients treated with a radiation therapy. Copyright © 2012 John Wiley & Sons, Ltd.
Yi Niu; Yingwei Peng
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-12-3
Journal Detail:
Title:  Statistics in medicine     Volume:  -     ISSN:  1097-0258     ISO Abbreviation:  Stat Med     Publication Date:  2012 Dec 
Date Detail:
Created Date:  2012-12-3     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8215016     Medline TA:  Stat Med     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2012 John Wiley & Sons, Ltd.
Department of Mathematics and Statistics, Queen's University, Kingston, ON, Canada, K7L 3N6; Cancer Care and Epidemiology, Queen's Cancer Research Institute, Kingston, ON, Canada, K7L 3N6.
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