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Analyzing Competing Risk Data Using the R timereg Package.
MedLine Citation:
PMID:  22707920     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
In this paper we describe flexible competing risks regression models using the comp.risk() function available in the timereg package for R based on Scheike et al. (2008). Regression models are specified for the transition probabilities, that is the cumulative incidence in the competing risks setting. The model contains the Fine and Gray (1999) model as a special case. This can be used to do goodness-of-fit test for the subdistribution hazards' proportionality assumption (Scheike and Zhang 2008). The program can also construct confidence bands for predicted cumulative incidence curves.We apply the methods to data on follicular cell lymphoma from Pintilie (2007), where the competing risks are disease relapse and death without relapse. There is important non-proportionality present in the data, and it is demonstrated how one can analyze these data using the flexible regression models.
Authors:
Thomas H Scheike; Mei-Jie Zhang
Publication Detail:
Type:  JOURNAL ARTICLE    
Journal Detail:
Title:  Journal of statistical software     Volume:  38     ISSN:  1548-7660     ISO Abbreviation:  -     Publication Date:  2011 Jan 
Date Detail:
Created Date:  2012-6-18     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101307056     Medline TA:  J Stat Softw     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Department of Biostatistics, University of Copenhagen, Øster Farimagsgade 5 B, P.O.B. 2099, DK-1014 Copenhagen K, Denmark, URL: http://staff.pubhealth.ku.dk/~ts/
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