Identifiability and Estimation of Marginal Survival Functions for Dependent Competing Risks Assuming the Copula is Known

Ming Zheng and John P. Klein
Additional contact information
Ming Zheng: The Ohio State University, Department of Statistics
John P. Klein: The Ohio State University, Department of Statistics

A chapter in Lifetime Data: Models in Reliability and Survival Analysis, 1996, pp 401-408 from Springer

Abstract: Abstract We show that if the copula between the two marginal distributions is known then the competing risks data is sufficient to identify the marginal survival function. An estimator is constructed to estimate the marginal survival functions based on an assumed copula. This estimator is shown to be consistent and to reduce to the Kaplan-Meier estimator when the death and censoring times are independent. Results of a simulation study are presented to compare this estimator to other estimators.

Keywords: Marginal Distribution; Archimedean Copula; Marginal Distribution Function; Censoring Time; Nonparametric Maximum Likelihood Estimator (search for similar items in EconPapers)
Date: 1996
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4757-5654-8_53

Ordering information: This item can be ordered from
http://www.springer.com/9781475756548

DOI: 10.1007/978-1-4757-5654-8_53

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().