The frailty approach is commonly used in reliability theory and survival analysis to model the dependence between lifetimes of individuals or components subject to common risk factors; according to this model the frailty (an unobservable random vector that describes environmental conditions) acts simultaneously on the hazard functions of the lifetimes. Some interesting conditions for stochastic comparisons between random vectors defined in accordance with these models have been described in the literature; in particular, comparisons between frailty models have been studied by assuming independence for the baseline survival functions and the corresponding environmental parameters. In this paper, a generalization of these models is developed, which assumes conditional dependence between the components of the random vector, and some conditions for stochastic comparisons are provided. Some examples of frailty models satisfying these conditions are also described.

Some Stochastic Properties of Conditionally Dependent Frailty Models / Fernandez Ponce, J. M.; Pellerey, Franco; Rodriguez Grignolo, M. R.. - In: STATISTICS. - ISSN 0233-1888. - STAMPA. - 50:3(2016), pp. 649-666. [10.1080/02331888.2015.1086350]

Some Stochastic Properties of Conditionally Dependent Frailty Models

PELLEREY, FRANCO;
2016

Abstract

The frailty approach is commonly used in reliability theory and survival analysis to model the dependence between lifetimes of individuals or components subject to common risk factors; according to this model the frailty (an unobservable random vector that describes environmental conditions) acts simultaneously on the hazard functions of the lifetimes. Some interesting conditions for stochastic comparisons between random vectors defined in accordance with these models have been described in the literature; in particular, comparisons between frailty models have been studied by assuming independence for the baseline survival functions and the corresponding environmental parameters. In this paper, a generalization of these models is developed, which assumes conditional dependence between the components of the random vector, and some conditions for stochastic comparisons are provided. Some examples of frailty models satisfying these conditions are also described.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2616128
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