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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/21320

Title: Extending the Archimedean copula methodology to model multivariate survival data grouped in clusters of variable size
Authors: Prenen, Leen
Braekers, Roel
Duchateau, Luc
Issue Date: 2017
Abstract: For the analysis of clustered survival data, two different types of models that take the association into account, are commonly used: frailty models and copula models. Frailty models assume that conditional on a frailty term for each cluster, the hazard functions of individuals within that cluster are independent. These unknown frailty terms with their imposed distribution are used to express the association between the different individuals in a cluster. Copula models on the other hand assume that the joint survival function of the individuals within a cluster is given by a copula function, evaluated in the marginal survival function of each individual. It is the copula function which describes the association between the lifetimes within a cluster. A major disadvantage of the present copula models over the frailty models is that the size of the different clusters must be small and equal in order to set up manageable estimation procedures for the different model parameters. We describe in this manuscript a copula model for clustered survival data where the clusters are allowed to be moderate to large and varying in size by considering the class of Archimedean copulas with completely monotone generator. We develop both one- and two-stage estimators for the different copula parameters. Furthermore we show the consistency and asymptotic normality of these estimators. Finally, we perform a simulation study to investigate the finite sample properties of the estimators. We illustrate the method on a data set containing the time to first insemination in cows, with cows clustered in herds.
Notes: Braekers, R (reprint author), Univ Hasselt, Interuniv Inst Biostatist & Stat Bioinformat, Martelarenlaan 42, B-3500 Hasselt, Belgium. roel.braekers@uhasselt.be
URI: http://hdl.handle.net/1942/21320
DOI: 1369-7412/17/79000
ISI #: 000394910700007
ISSN: 1369-7412
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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