De Gruttola V, Lagakos S W
Harvard University, Boston, Massachusetts.
Biometrics. 1989 Mar;45(1):1-11.
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.
本文提出了非参数和弱结构化参数方法，用于分析生存数据，其中时间原点和失效事件都可能是右删失或区间删失的。此类数据出现在人类免疫缺陷病毒（HIV）的临床研究中，此时仅在几个时间点观察患者的感染情况和临床状态。所提出的方法推广了Turnbull（1976年，《皇家统计学会杂志》，B辑38卷，290 - 295页）针对单删失单变量数据提出的自一致性算法，并通过一项对因受污染血液因子感染HIV的血友病患者的研究结果进行了说明。
