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A two-stage estimator of the dependence parameter for the Clayton-Oakes model
1Department of Epidemiology and Biostatistics, University of California, San Francisco 94143, USA. david@biostat.ucsf.edu
Abstract:
This paper describes the properties of a two-stage estimator of the dependence parameter in the Clayton-Oakes multivariate failure time model. The parameter is estimated from a likelihood function in which the marginal hazard functions are replaced by estimates. The method extends the approach of Shih and Louis (1995) and Genest, Ghoudi and Rivest (1995) to allow the marginal hazard for failure times to follow a stratified Cox (1972) model. The method is computationally simple and under mild regularity conditions produces a consistent, asymptotically normal estimator.
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