Journal
SCANDINAVIAN JOURNAL OF STATISTICS
Volume 30, Issue 3, Pages 509-521Publisher
WILEY
DOI: 10.1111/1467-9469.00345
Keywords
Clayton-Oakes model; marginal proportional hazards; multivariate failure times; semiparametric likelihood estimation
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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 this paper, we consider the Clayton-Oakes model with marginal proportional hazards and use the full model structure to improve on efficiency compared with the independence analysis. We derive a likelihood based estimating equation for the regression parameters as well as for the correlation parameter of the model. We give the large sample properties of the estimators arising from this estimating equation. Finally, we investigate the small sample properties of the estimators through Monte Carlo simulations.
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