Gaining efficiency via weighted estimators for multivariate failure time data

Jianqing Fan, Yong Zhou, Jianwen Cai, Min Chen

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Multivariate failure time data arise frequently in survival analysis. A commonly used technique is the working independence estimator for marginal hazard models. Two natural questions are how to improve the efficiency of the working independence estimator and how to identify the situations under which such an estimator has high statistical efficiency. In this paper, three weighted estimators are proposed based on three different optimal criteria in terms of the asymptotic covariance of weighted estimators. Simplified close-form solutions are found, which always outperform the working independence estimator. We also prove that the working independence estimator has high statistical efficiency, when asymptotic covariance of derivatives of partial log-likelihood functions is nearly exchangeable or diagonal. Simulations are conducted to compare the performance of the weighted estimator and working independence estimator. A data set from Busselton population health surveys is analyzed using the proposed estimators.

Original languageEnglish (US)
Pages (from-to)1113-1128
Number of pages16
JournalScience in China, Series A: Mathematics
Issue number6
StatePublished - Jun 2009

All Science Journal Classification (ASJC) codes

  • General Mathematics


  • Marginal hazard model
  • Optimal weight
  • Pseudo-partial likelihood
  • Working independence estimator


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