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A New Semiparametric Estimation Method for Accelerated Hazards Mixture Cure Model.
MedLine Citation:
PMID:  23293406     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
The semiparametric accelerated hazards mixture cure model provides a useful alternative to analyze survival data with a cure fraction if covariates of interest have a gradual effect on the hazard of uncured patients. However, the application of the model may be hindered by the computational intractability of its estimation method due to non-smooth estimating equations involved. We propose a new semiparametric estimation method based on a smooth estimating equation for the model and demonstrate that the new method makes the parameter estimation more tractable without loss of efficiency. The proposed method is used to fit the model to a SEER breast cancer data set.
Authors:
Jiajia Zhang; Yingwei Peng; Haifen Li
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Publication Detail:
Type:  JOURNAL ARTICLE    
Journal Detail:
Title:  Computational statistics & data analysis     Volume:  59     ISSN:  0167-9473     ISO Abbreviation:  Comput Stat Data Anal     Publication Date:  2013 Mar 
Date Detail:
Created Date:  2013-1-7     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  100960938     Medline TA:  Comput Stat Data Anal     Country:  -    
Other Details:
Languages:  ENG     Pagination:  95-102     Citation Subset:  -    
Affiliation:
Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC 29208, USA.
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