Analysis of Doubly-Censored Survival Data, with Application to AIDS

This paper proposes nonparametric and weakly structured parametric methods for analyzing survival data in which both the time origin and the failure event can be right- or interval-censored. Such data arise in clinical investigations of the human immunodeficiency virus (HIV) when the infection and c...

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Bibliographic Details
Published in:Biometrics 1989-03, Vol.45 (1), p.1-11
Main Authors: De Gruttola, Victor, Lagakos, Stephen W.
Format: Article
Language:English
Subjects:
Acquired Immunodeficiency Syndrome - etiology
Acquired Immunodeficiency Syndrome - mortality
AIDS
AIDS/HIV
Algorithms
Biometrics
Biometry
Censorship
Critical values
Data Interpretation, Statistical
Estimators
Factor VIII - adverse effects
Hemophilia A - drug therapy
HIV
Humans
Infections
Maximum likelihood estimation
Parametric models
Retrospective Studies
Saddle points
Sampling Studies
Time Factors
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Summary:This paper proposes nonparametric and weakly structured parametric methods for analyzing survival data in which both the time origin and the failure event can be right- or interval-censored. Such data arise in clinical investigations of the human immunodeficiency virus (HIV) when the infection and clinical status of patients are observed only at several time points. The proposed methods generalize the self-consistency algorithm proposed by Turnbull (1976, Journal of the Royal Statistical Society, Series B 38, 290-295) for singly-censored univariate data, and are illustrated with the results from a study of hemophiliacs who were infected with HIV by contaminated blood factor.
ISSN:0006-341X
1541-0420
DOI:10.2307/2532030