Empirical copulas for consecutive survival data

E. Strzalkowska-Kominiak () and W. Stute ()

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2013, vol. 22, issue 4, 688-714

Abstract: In the analysis of medical data the whole lifetime is often split into pieces characterizing the various stages in the development of a chronical disease. In this paper we provide a nonparametric copula function estimator for two consecutive survival data which are subject to truncation and right censorship. We also discuss an extension of Spearman’s Rho and Kendall’s Tau to the present situation. Copyright Sociedad de Estadística e Investigación Operativa 2013

Keywords: Consecutive survival data; Nonparametric copulas; Tests for independence; 62G30; 62N01; 62N02; 62N03 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://hdl.handle.net/10.1007/s11749-013-0339-1 (text/html)
Access to full text is restricted to subscribers.

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:testjl:v:22:y:2013:i:4:p:688-714

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/11749/PS2

DOI: 10.1007/s11749-013-0339-1

Access Statistics for this article

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research is currently edited by Alfonso Gordaliza and Ana F. Militino

More articles in TEST: An Official Journal of the Spanish Society of Statistics and Operations Research from Springer, Sociedad de Estadística e Investigación Operativa
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().