Fitting competing risks with an assumed copula.

Abstract:

:We propose a fully parametric model for the analysis of competing risks data where the types of failure may not be independent. We show how the dependence between the cause-specific survival times can be modelled with a copula function. Features include: identifiability of the problem; accessible understanding of the dependence structures; and flexibility in choosing marginal survival functions. The model is constructed in such a way that it allows us to adjust for concomitant variables and for a dependence parameter to assess the effects of these on each marginal survival model and on the relationship between the causes of death. The methods are applied to a prostate cancer data set. We find that, with the copula model, more accurate inferences are obtained than with the use of a simpler model such as the independent competing risks approach.

journal_name

Stat Methods Med Res

authors

Escarela G,Carrière JF

doi

10.1191/0962280203sm335ra

subject

Has Abstract

pub_date

2003-08-01 00:00:00

pages

333-49

issue

4

eissn

0962-2802

issn

1477-0334

journal_volume

12

pub_type

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