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Constrained mixture models in competing risks problems
Author(s) -
Ng S. K.,
McLachlan G. J.,
McGiffin D. C.,
O'Brien M. F.
Publication year - 1999
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/(sici)1099-095x(199911/12)10:6<753::aid-env388>3.0.co;2-k
Subject(s) - parametric statistics , dependency (uml) , computer science , component (thermodynamics) , aortic valve replacement , mixture model , valve replacement , prosthesis , mathematics , medicine , statistics , artificial intelligence , cardiology , stenosis , thermodynamics , physics
We consider the problem of modelling the failure‐time distribution, where failure is due to two distinct causes. One approach is to adopt a two‐component mixture model where the components correspond to the two different causes of failure. However, routine application of this approach with typical parametric forms for the component densities proves to be inadequate in modelling the time to a re‐replacement operation or death after the initial replacement of the aortic valve in the heart by a prosthesis, such as a xenograft valve. Hence we consider modifications to the usual mixture model approach to handle situations where there exists a strong dependency between the failure times of the distinct causes. With these modifications, a suitable model is able to be provided for the distribution of the time to a re‐replacement operation conditional on the age of the patient at the time of the initial replacement operation. The estimate so obtained by the probability that a patient of a given age will undergo a re‐replacement operation provides a useful guide to heart surgeons on the type of valve to be used in view of the patient's age. Copyright © 1999 John Wiley & Sons, Ltd.