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

Overview

Journal Biometrics

Publisher Oxford University Press

Specialty Public Health

Date 1989 Mar 1

PMID 2497809

Citations 38

Authors

V de Gruttola

S W Lagakos

Affiliations

Soon will be listed here.

Abstract

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.

Citing Articles

Multiple imputation strategies for missing event times in a multi-state model analysis.

Curnow E, Hughes R, Birnie K, Tilling K, Crowther M Stat Med. 2024; 43(6):1238-1255.

PMID: 38258282 PMC: 7616776. DOI: 10.1002/sim.10011.

A progressive three-state model to estimate time to cancer: a likelihood-based approach.

Akwiwu E, Klausch T, Jodal H, Carvalho B, Loberg M, Kalager M BMC Med Res Methodol. 2022; 22(1):179.

PMID: 35761181 PMC: 9235269. DOI: 10.1186/s12874-022-01645-2.

Efficient empirical likelihood inference for recovery rate of COVID19 under double-censoring.

Hu J, Liang W, Dai H, Bao Y J Stat Plan Inference. 2022; 221:172-187.

PMID: 35573146 PMC: 9077865. DOI: 10.1016/j.jspi.2022.04.005.

Maximum likelihood estimation for the proportional odds model with mixed interval-censored failure time data.

Zhu L, Tong X, Cai D, Li Y, Sun R, Srivastava D J Appl Stat. 2021; 48(8):1496-1512.

PMID: 34349336 PMC: 8330546. DOI: 10.1080/02664763.2020.1789077.

Parameter estimation of the incubation period of COVID-19 based on the doubly interval-censored data model.

Yin M, Zhu Q, Lu X Nonlinear Dyn. 2021; 106(2):1347-1358.

PMID: 34177117 PMC: 8211977. DOI: 10.1007/s11071-021-06587-w.