Nonparametric estimators of the bivariate survival function under simplified censoring conditions

Weijing Wang*, Martin T. Wells

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

New bivariate survival function estimators are proposed in the case where the dependence relationship between the censoring variables are modelled. Specific examples include the cases when censoring variables are univariate, mutually independent or specified by a marginal model. Large sample properties of the proposed estimators are discussed. The finite sample performance of the proposed estimators compared with other fully nonparametric estimators is studied via simulations. A real data example is given.

Original languageEnglish
Pages (from-to)863-880
Number of pages18
JournalBiometrika
Volume84
Issue number4
DOIs
StatePublished - 1 Dec 1997

Keywords

  • Archimedean copula
  • Bivariate failure time data
  • Independent censoring
  • Marginal modelling
  • Univariate censoring

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