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Reduced rank hazard regression with fixed and time-varying effects of the covariates.
MedLine Citation:
PMID:  23203917     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Modelling survival data from long-term follow-up studies presents challenges. The commonly used proportional hazards model should be extended to account for dynamic behaviour of the effects of fixed covariates. This work illustrates the use of reduced rank models in survival data, where some of the covariate effects are allowed to behave dynamically in time and some as fixed. Time-varying effects of the covariates can be fitted by using interactions of the fixed covariates with flexible transformations of time based on b-splines. To avoid overfitting, a reduced rank model will restrict the number of parameters, resulting in a more sensible fit to the data. This work presents the basic theory and the algorithm to fit such models. An application to breast cancer data is used for illustration of the suggested methods.
Authors:
Aris Perperoglou
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-12-2
Journal Detail:
Title:  Biometrical journal. Biometrische Zeitschrift     Volume:  -     ISSN:  1521-4036     ISO Abbreviation:  Biom J     Publication Date:  2012 Dec 
Date Detail:
Created Date:  2012-12-3     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7708048     Medline TA:  Biom J     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
© 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Affiliation:
Department of Mathematical Sciences, University of Essex, Colchester, CO4 3SQ, UK.
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