Sample Size Corrections for the Maximum Partial Likelihood Estimator

Abstract

In this paper, resampling methods, namely the jackknife and the bootstrap, are considered for bias evaluation and correction of maximum partial likelihood estimators. A complete set of Monte Carlo simulations compare the proposed approaches with formulae recently proposed for bias correction to order n ⁻¹. The results indicate a competitive performance for these methods.

Key Words:

• Maximum partial likelihood estimate
• Censored data
• Bootstrap
• Jackknife

Acknowledgments

The research of Frederico R. B. Cruz has been partially funded by the CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) of the Ministry for Science and Technology of Brazil, grants 301809/96-8 and 201046/94-6, the FAPEMIG (Fundação de Amparo à Pesquisa do Estado de Minas Gerais), grants CEX-289/98 and CEX-855/98, and the PRPq-UFMG, grant 4081-UFMG/RTR/ FUNDO/PRPq/99. The work of Enrico A. Colosimo has been partially funded by the CNPq, grant 300249/1994-2.