Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2008 Mar 1;95(1):221-232.
doi: 10.1093/biomet/asm091.

Non-parametric estimation of bivariate failure time associations in the presence of a competing risk

Karen Bandeen-Roche  1 , Jing Ning
Affiliations

Non-parametric estimation of bivariate failure time associations in the presence of a competing risk

Karen Bandeen-Roche et al. Biometrika. .

Abstract

Most research on the study of associations among paired failure times has either assumed time invariance or been based on complex measures or estimators. Little has accommodated competing risks. This paper targets the conditional cause-specific hazard ratio, henceforth called the cause-specific cross ratio, a recent modification of the conditional hazard ratio designed to accommodate competing risks data. Estimation is accomplished by an intuitive, non-parametric method that localizes Kendall's tau. Time variance is accommodated through a partitioning of space into 'bins' between which the strength of association may differ. Inferential procedures are developed, small-sample performance is evaluated and the methods are applied to the investigation of familial association in dementia onset.

PubMed Disclaimer

References

    1. Bandeen-roche K, Liang KY. Modelling multivariate failure time associations in the presence of a competing risk. Biometrika. 2002;89:299–314. - PMC - PubMed
    1. Barbe P, Genest C, Ghoudi K, RÁillard B. On Kendall’s process. J. Multivariate Anal. 1996;58:197–229.
    1. Benichou J, Gail MH. Estimates of absolute cause-specific risk in cohort studies. Biometrics. 1990;46:813–826. - PubMed
    1. Breitner JCS, Wyse BW, Anthony JC, Welsh-Bohmer KA, Steffens DC, Norton MC, Tschanz JT, Plassman BL, Meyer MR, Skoog I, Khachaturian A. APOE-ϵ4 count predicts age when prevalence of AD increases, then declines: The Cache County Study. Neurology. 1999;53:321–331. - PubMed
    1. Chen MC, Bandeen-Roche K. A diagnostic for association in bivariate survival models. Lifetime Data Anal. 2005;11:245–264. - PubMed