多变量纵向和生存数据的半参数潜伏类模型。

IF 3.2 1区 数学 Q1 STATISTICS & PROBABILITY Annals of Statistics Pub Date : 2022-02-01 Epub Date: 2022-02-16 DOI:10.1214/21-aos2117
Kin Yau Wong, Donglin Zeng, D Y Lin
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引用次数: 0

摘要

在长期随访研究中,经常收集多变量反应变量的重复测量数据以及某一事件发生的时间数据。为了联合分析这些纵向数据和生存时间,我们提出了一类一般的半参数潜在类模型,该模型适应了纵向结果和生存结果之间具有灵活依赖结构的异质性研究人群。我们将非参数最大似然估计与筛估计相结合,并设计了一种有效的EM算法来实现所提出的方法。我们通过新颖地使用现代经验过程理论、筛估计理论和半参数效率理论,建立了所提出的估计量的渐近性质。最后,我们通过广泛的模拟研究证明了所提出方法的优势,并为社区动脉粥样硬化风险研究提供了应用。
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SEMIPARAMETRIC LATENT-CLASS MODELS FOR MULTIVARIATE LONGITUDINAL AND SURVIVAL DATA.

In long-term follow-up studies, data are often collected on repeated measures of multivariate response variables as well as on time to the occurrence of a certain event. To jointly analyze such longitudinal data and survival time, we propose a general class of semiparametric latent-class models that accommodates a heterogeneous study population with flexible dependence structures between the longitudinal and survival outcomes. We combine nonparametric maximum likelihood estimation with sieve estimation and devise an efficient EM algorithm to implement the proposed approach. We establish the asymptotic properties of the proposed estimators through novel use of modern empirical process theory, sieve estimation theory, and semiparametric efficiency theory. Finally, we demonstrate the advantages of the proposed methods through extensive simulation studies and provide an application to the Atherosclerosis Risk in Communities study.

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来源期刊
Annals of Statistics
Annals of Statistics 数学-统计学与概率论
CiteScore
9.30
自引率
8.90%
发文量
119
审稿时长
6-12 weeks
期刊介绍: The Annals of Statistics aim to publish research papers of highest quality reflecting the many facets of contemporary statistics. Primary emphasis is placed on importance and originality, not on formalism. The journal aims to cover all areas of statistics, especially mathematical statistics and applied & interdisciplinary statistics. Of course many of the best papers will touch on more than one of these general areas, because the discipline of statistics has deep roots in mathematics, and in substantive scientific fields.
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