Analysis of competing risks survival data when some failure types are missing

Goetghebeur, E; Ryan, L

Analysis of competing risks survival data when some failure types are missing

Goetghebeur, E Ryan, L

Permalink

Publication Type:: Journal Article
Citation:: Biometrika, 1995, 82 (4), pp. 821 - 833
Issue Date:: 1995-12-01

Closed Access

	Filename	Description	Size
	2012000310OK.pdf		1.11 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Goetghebeur, E	en_US
dc.contributor.author	Ryan, L https://orcid.org/0000-0001-5957-2490	en_US
dc.date.issued	1995-12-01	en_US
dc.identifier.citation	Biometrika, 1995, 82 (4), pp. 821 - 833	en_US
dc.identifier.issn	0006-3444	en_US
dc.identifier.uri	http://hdl.handle.net/10453/26225
dc.description.abstract	We propose a method to analyse competing risks survival data when failure types are missing for some individuals. Our approach is based on a standard proportional hazards structure for each of the failure types, and involves the solution to estimating equations. We present consistent and asymptotically normal estimators of the regression coefficients and related score tests. An appealing feature is that individuals with known failure types make the same contributions as they would to a standard proportional hazards analysis. Contributions of individuals with unknown failure types are weighted according to the probability that they failed from the cause of interest. Efficiency and robustness are discussed. Results are illustrated with data from a breast cancer trial. © 1995 Biometrika Trust.	en_US
dc.relation.ispartof	Biometrika	en_US
dc.relation.isbasedon	10.1093/biomet/82.4.821	en_US
dc.subject.classification	Statistics & Probability	en_US
dc.title	Analysis of competing risks survival data when some failure types are missing	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	82	en_US
utslib.for	010402 Biostatistics	en_US
utslib.for	0103 Numerical and Computational Mathematics	en_US
utslib.for	0104 Statistics	en_US
utslib.for	1403 Econometrics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	closed_access
pubs.issue	4	en_US
pubs.publication-status	Published	en_US
pubs.volume	82	en_US

Abstract:

We propose a method to analyse competing risks survival data when failure types are missing for some individuals. Our approach is based on a standard proportional hazards structure for each of the failure types, and involves the solution to estimating equations. We present consistent and asymptotically normal estimators of the regression coefficients and related score tests. An appealing feature is that individuals with known failure types make the same contributions as they would to a standard proportional hazards analysis. Contributions of individuals with unknown failure types are weighted according to the probability that they failed from the cause of interest. Efficiency and robustness are discussed. Results are illustrated with data from a breast cancer trial. © 1995 Biometrika Trust.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/26225