Methods for bounding the marginal survival distribution
- 30 September 1995
- journal article
- research article
- Published by Wiley in Statistics in Medicine
- Vol. 14 (18) , 1985-1998
- https://doi.org/10.1002/sim.4780141805
Abstract
For time to event data with many potential failure types, one cannot uniquely determine the distribution of time to a specific event type, or marginal survival distribution, in the case where event types are mutually exclusive. In this paper we discuss several methods for estimating functions that bound the non‐identifiable marginal survival distribution in the competing risks problem. We compute and compare bounds for data simulated from two bivariate survival distributions. Results show that the methods provide a suitable estimate of the marginal survival probability when one has specified dependence correctly. Data from a large clinical trial for breast cancer illustrate the methods.Keywords
This publication has 24 references indexed in Scilit:
- On the Use of Cause-Specific Failure and Conditional Failure Probabilities: Examples from Clinical Oncology DataJournal of the American Statistical Association, 1993
- Testing the assumption of independence of truncation time and failure timeBiometrika, 1990
- A Class of Multivariate Failure Time DistributionsBiometrika, 1986
- Dependent competing risks and summary survival curvesBiometrika, 1983
- Rank tests for association with right censored dataBiometrika, 1982
- An investigation of Kendall's τ modified for censored data with applicationsJournal of Statistical Planning and Inference, 1980
- A Bivariate Extension of the Exponential DistributionJournal of the American Statistical Association, 1961