Asymptotically efficient estimation of a survival function in the missing censoring indicator model

Author: Sundarraman Subramanian

Source: Journal of Nonparametric Statistics, Volume 16, Number 5, October 2004 , pp. 797-817(21)

Publisher: Taylor and Francis Ltd

Abstract:

We propose and analyze a new estimator of a survival function in the random censorship model when the censoring indicator is missing at random for some study subjects. The proposed approach appeals to a known representation for the survival function, expressible as a smooth functional of a certain conditional probability and the cumulative hazard function of the observed minimum. Well-known estimators are substituted into this representation leading to a simple estimator of the survival function. The new estimator, whose asymptotic variance reduces to that of the Kaplan-Meier estimator when all the censoring indicators are observed, is shown to achieve the efficiency bound derived by van der Laan and McKeague.

Document Type: Research article

DOI: http://dx.doi.org/10.1080/10485250410001681176

Publication date: 2004-10-01

Related content

• In this: publication
• By this: publisher
• In this Subject: Mathematics and Statistics
• By this author: Sundarraman Subramanian

Website © Publishing Technology. Article copyright remains with the publisher, society or author(s) as specified within the article.

• Terms and conditions
• Privacy policy
• Information for advertisers