Association analyses of clustered competing risks data via cross hazard ratio

Yu Cheng, Jason P. Fine, Karen Bandeen-Roche

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Bandeen-Roche and Liang (2002, Modelling multivariate failure time associations in the presence of a competing risk. Biometrika 89, 299-314.) tailored Oakes (1989, Bivariate survival models induced by frailties. Journal of the American Statistical Association 84, 487-493.)'s conditional hazard ratio to evaluate cause-specific associations in bivariate competing risks data. In many population-based family studies, one observes complex multivariate competing risks data, where the family sizes may be >2, certain marginals may be exchangeable, and there may be multiple correlated relative pairs having a given pairwise association. Methods for bivariate competing risks data are inadequate in these settings. We show that the rank correlation estimator of Bandeen-Roche and Liang (2002) extends naturally to general clustered family structures. Consistency, asymptotic normality, and variance estimation are easily obtained with U-statistic theories. A natural by-product is an easily implemented test for constancy of the association over different time regions. In the Cache County Study on Memory in Aging, familial associations in dementia onset are of interest, accounting for death prior to dementia. The proposed methods using all available data suggest attenuation in dementia associations at later ages, which had been somewhat obscured in earlier analyses.

Original languageEnglish (US)
Pages (from-to)82-92
Number of pages11
Issue number1
StatePublished - Jan 2010


  • Cause-specific hazard ratio
  • Concordance estimator
  • Dependent censoring
  • Exchangeable clustered data
  • Time-varying association

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


Dive into the research topics of 'Association analyses of clustered competing risks data via cross hazard ratio'. Together they form a unique fingerprint.

Cite this