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Applying Cox Regression to Competing Risks

Authors: M, Lunn; D, McNeil;

Applying Cox Regression to Competing Risks

Abstract

Two methods are given for the joint estimation of parameters in models for competing risks in survival analysis. In both cases Cox's proportional hazards regression model is fitted using a data duplication method. In principle either method can be used for any number of different failure types, assuming independent risks. Advantages of the augmented data approach are that it limits over-parametrisation and it runs immediately on existing software. The methods are used to reanalyse data from two well-known published studies, providing new insights.

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Keywords

Graft Rejection, Male, Analysis of Variance, Models, Statistical, Time Factors, Prostatic Neoplasms, Survival Analysis, Risk Factors, Neoplasms, Heart Transplantation, Humans, Diethylstilbestrol, Mathematics, Software, Proportional Hazards Models, Randomized Controlled Trials as Topic

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    897
    popularity
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    Top 0.1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
897
Top 0.1%
Top 0.1%
Top 10%
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