An estimating equation for parametric shared frailty models with marginal additive hazards

Christian Bressen Pipper; Torben Martinussen

doi:10.1046/j.1369-7412.2003.05305.x

An estimating equation for parametric shared frailty models with marginal additive hazards

Christian Bressen Pipper, Torben Martinussen

13 Citations (Scopus)

Abstract

Multivariate failure time data arise when data consist of clusters in which the failure times may be dependent. A popular approach to such data is the marginal proportional hazards model with estimation under the working independence assumption. In some contexts, however, it may be more reasonable to use the marginal additive hazards model. We derive asymptotic properties of the Lin and Ying estimators for the marginal additive hazards model for multivariate failure time data. Furthermore we suggest estimating equations for the regression parameters and association parameters in parametric shared frailty models with marginal additive hazards by using the Lin and Ying estimators. We give the large sample properties of the estimators arising from these estimating equations and investigate their small sample properties by Monte Carlo simulation. A real example is provided for illustration

Original language	English
Journal	Journal of The Royal Statistical Society Series B-statistical Methodology
Volume	66
Issue number	1
Pages (from-to)	207-220
Number of pages	14
ISSN	1369-7412
DOIs	https://doi.org/10.1046/j.1369-7412.2003.05305.x
Publication status	Published - 2004

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An estimating equation for parametric shared frailty models with marginal additive hazards

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