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Nonparametric predictive pairwise comparison with competing risks.

Coolen-Maturi, T. (2014) 'Nonparametric predictive pairwise comparison with competing risks.', Reliability engineering & system safety., 132 . pp. 146-153.


In reliability, failure data often correspond to competing risks, where several failure modes can cause a unit to fail. This paper presents nonparametric predictive inference (NPI) for pairwise comparison with competing risks data, assuming that the failure modes are independent. These failure modes could be the same or different among the two groups, and these can be both observed and unobserved failure modes. NPI is a statistical approach based on few assumptions, with inferences strongly based on data and with uncertainty quantified via lower and upper probabilities. The focus is on the lower and upper probabilities for the event that the lifetime of a future unit from one group, say Y, is greater than the lifetime of a future unit from the second group, say X. The paper also shows how the two groups can be compared based on particular failure mode(s), and the comparison of the two groups when some of the competing risks are combined is discussed.

Item Type:Article
Keywords:Competing risks, Reliability, Pairwise comparison, Nonparametric predictive inference, Lower and upper probabilities, Lower and upper survival functions, Right-censored data.
Full text:(AM) Accepted Manuscript
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Publisher statement:NOTICE: this is the author’s version of a work that was accepted for publication in Reliability Engineering & System Safety. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Reliability Engineering & System Safety, 132, 2014, 10.1016/j.ress.2014.07.014.
Date accepted:17 July 2014
Date deposited:05 August 2014
Date of first online publication:30 July 2014
Date first made open access:No date available

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