左删失纵向数据和生存数据的稳健联合建模，并将其应用于艾滋病疫苗研究。

IF 1.3 4区数学 Q2 STATISTICS & PROBABILITY

Annals of Applied Statistics Pub Date : 2023-06-01 Epub Date: 2023-05-01 DOI:10.1214/22-aoas1656

Tingting Yu, Lang Wu, Jin Qiu, Peter B Gilbert

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引用次数: 0

摘要

在对纵向数据和生存数据进行联合建模时，纵向数据可能比较复杂，因为它们可能包含异常值，也可能会被留存。受一项艾滋病疫苗研究的启发，我们提出了一种用于纵向数据和生存数据联合建模的稳健方法，其中对 b 型离群值使用多元 t 分布，对 e 型离群值使用 M 估计器来处理纵向数据中的离群值。我们还提出了一种计算效率高的近似似然推断方法。我们通过模拟研究对提出的方法进行了评估。根据提出的模型和方法，我们分析了 HIV 疫苗数据，发现纵向生物标志物与 HIV 感染风险之间存在密切联系。

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Robust joint modelling of left-censored longitudinal data and survival data with application to HIV vaccine studies.

In jointly modelling longitudinal and survival data, the longitudinal data may be complex in the sense that they may contain outliers and may be left censored. Motivated from an HIV vaccine study, we propose a robust method for joint models of longitudinal and survival data, where the outliers in longitudinal data are addressed using a multivariate t-distribution for b-outliers and using an M-estimator for e-outliers. We also propose a computationally efficient method for approximate likelihood inference. The proposed method is evaluated by simulation studies. Based on the proposed models and method, we analyze the HIV vaccine data and find a strong association between longitudinal biomarkers and the risk of HIV infection.

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来源期刊

Annals of Applied Statistics 社会科学-统计学与概率论

CiteScore

3.10

自引率

5.60%

发文量

131

审稿时长

6-12 weeks

期刊介绍： Statistical research spans an enormous range from direct subject-matter collaborations to pure mathematical theory. The Annals of Applied Statistics, the newest journal from the IMS, is aimed at papers in the applied half of this range. Published quarterly in both print and electronic form, our goal is to provide a timely and unified forum for all areas of applied statistics.