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First-Passage-Time Models for Duration Data: Regression Structures and Competing Risks
G. A. Whitmore
Journal of the Royal Statistical Society. Series D (The Statistician)
Vol. 35, No. 2, Special Issue: Statistical Modelling (1986), pp. 207-219
Stable URL: http://www.jstor.org/stable/2987525
Page Count: 13
You can always find the topics here!Topics: Failure modes, Statistical estimation, Censorship, Divorce, Brownian motion, Gaussian distributions, Kaplan meiers estimate, Statistical models, Censored data, Stochastic processes
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Recent research has demonstrated the practical and theoretical value of using first-passage-time distributions as models of duration data (e.g., equipment lives, hospital stays, employee service times). The inverse Gaussian distribution is the principal example of this type. Methods have been developed for handling regression structures and censoring for the inverse Gaussian model in order to cope with these features in real data. This paper discusses the use of first-passage-time distributions connected with multidimensional Brownian motion as models for duration data which are subject to competing risks (i.e., multiple failure modes). The approach is a natural extension of the regression methodology for censored inverse Gaussian data published previously by the author. Several case applications of the competing-risks formulation are presented.
Journal of the Royal Statistical Society. Series D (The Statistician) © 1986 Royal Statistical Society