Redistribution algorithms for censored data

Rebecca A. Betensky

doi:10.1016/S0167-7152(99)00127-3

Redistribution algorithms for censored data

Rebecca A. Betensky

Global Public Health

Research output: Contribution to journal › Article › peer-review

Abstract

Efron (Proceedings of the Fifth Berkeley Symposium, Vol. 4, University of California Press, Berkeley, CA, pp. 831-853) and Dinse (Amer. Statist. 39, 1985, 299-300) proposed redistribution of mass algorithms for survivor function estimation from right censored data. Dinse's algorithm is easily extended to survivor function estimation from interval censored data and is further extended to incorporate information on disease markers.

Original language	English (US)
Pages (from-to)	385-389
Number of pages	5
Journal	Statistics and Probability Letters
Volume	46
Issue number	4
DOIs	https://doi.org/10.1016/S0167-7152(99)00127-3
State	Published - Feb 15 2000

Keywords

Kaplan-Meier estimator
Nonparametric maximum likelihood estimator
Self-consistent estimator
Survivor function

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1016/S0167-7152(99)00127-3

Cite this

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AB - Efron (Proceedings of the Fifth Berkeley Symposium, Vol. 4, University of California Press, Berkeley, CA, pp. 831-853) and Dinse (Amer. Statist. 39, 1985, 299-300) proposed redistribution of mass algorithms for survivor function estimation from right censored data. Dinse's algorithm is easily extended to survivor function estimation from interval censored data and is further extended to incorporate information on disease markers.

KW - Kaplan-Meier estimator

KW - Nonparametric maximum likelihood estimator

KW - Self-consistent estimator

KW - Survivor function

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ER -

Redistribution algorithms for censored data

Abstract

Keywords

ASJC Scopus subject areas

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