NONPARAMETRIC-ESTIMATION AND DOUBLY-CENSORED DATA - GENERAL IDEAS AND APPLICATIONS TO AIDS
NONPARAMETRIC-ESTIMATION AND DOUBLY-CENSORED DATA - GENERAL IDEAS AND APPLICATIONS TO AIDS
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DOI：
10.1002/sim.4780131917
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发表时间：
1994-10-15
影响因子：
2
通讯作者：
JEWELL, NP
中科院分区：
文献类型：
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作者：
JEWELL, NP
在许多人类免疫缺陷病毒（HIV）疾病的流行病学研究中，人们的兴趣集中在两个事件之间的时间间隔长度的分布上。在许多这样的情况下，这种分布的属性的统计估计是复杂的事实，即两个事件的时间的观察受到intervalcensoring，使事件之间的时间长度从来没有观察到准确。继DeGruttola和Lagakos之后，我们称此类数据为双重审查。朱厄尔，Malani和Vittinghoff证明了在一定的假设条件下，对于特定的双删失数据结构，区间长度分布的非参数极大似然估计等价于混合分布的非参数估计.在这里，我们将这些想法扩展到各种其他类型的双删失数据。我们考虑将这些方法应用于通过调查艾滋病毒疾病的自然史而产生的各种研究，特别注意估计个体感染（指示病例）和将艾滋病毒传播给其性伴侣之间的时间分布。
In many epidemiologic studies of human immunodeficiency virus (HIV) disease, interest focuses on the distribution of the length of the interval of time between two events. In many such cases, statistical estimation of properties of this distribution is complicated by the fact that observation of the times of both events is subject to intervalcensoring so that the length of time between the events is never observed exactly. Following DeGruttola and Lagakos, we call such data doubly-censored. Jewell, Malani and Vittinghoff showed that, with certain assumptions and for a particular doubly-censored data structure, non-parametric maximum likelihood estimation of the interval length distribution is equivalent to non-parametric estimation of a mixing distribution. Here, we extend these ideas to various other kinds of doubly-censored data. We consider application of the methods to various studies generated by investigations into the natural history of HIV disease with particular attention given to estimation of the distribution of time between infection of an individual (an index case) and transmission of HIV to their sexual partner.