On nonparametric maximum likelihood estimation with double truncation

J Xiao and M G Hudgens

Biometrika, 2019, vol. 106, issue 4, 989-996

Abstract: SummaryDoubly truncated survival data arise if failure times are observed only within certain time intervals. The nonparametric maximum likelihood estimator is widely used to estimate the underlying failure time distribution. Using a directed graph representation of the data suggested by Vardi (1985), a certain graphical condition holds if and only if the nonparametric maximum likelihood estimate exists and is unique. If this condition does not hold, then such an estimate may exist but need not be unique, so another graphical condition is proposed to check whether such an estimate exists. The conditions are simple to check using existing graphical software. Reanalysis of an AIDS incubation time dataset shows that a nonparametric maximum likelihood estimate does not exist for these data.

Keywords: Graph; Nonparametric estimator; Truncation (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1093/biomet/asz038 (application/pdf)
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:oup:biomet:v:106:y:2019:i:4:p:989-996.

Ordering information: This journal article can be ordered from
https://academic.oup.com/journals

Access Statistics for this article

Biometrika is currently edited by Paul Fearnhead

More articles in Biometrika from Biometrika Trust Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK.
Bibliographic data for series maintained by Oxford University Press ().