Model Selection and Semiparametric Inference for Bivariate Failure-Time Data

Wei-Jing Wang*, Martin T. Wells

*Corresponding author for this work

Research output: Contribution to journalArticle

156 Scopus citations

Abstract

We propose model selection procedures for bivariate survival models for censored data generated by the Archimedean copula family. In route to constructing the selection methodology, we develop estimates of some time-dependent association measures, including estimates of the local and global Kendall's tau, local odds ratio, and other measures defined throughout the literature. We propose a goodness-of-fit-based model selection methodology as well as a graphical approach. We show that the proposed methods have desirable asymptotic properties and perform well in finite samples.

Original languageEnglish
Pages (from-to)62-72
Number of pages11
JournalJournal of the American Statistical Association
Volume95
Issue number449
DOIs
StatePublished - 1 Mar 2000

Keywords

  • Archimedean copula
  • Bivariate survival function
  • Frailty distribution
  • Kendall's tau
  • Model selection
  • Odds ratio estimation
  • Time-dependent association

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