ROBUST JOINT MODELLING OF LEFT-CENSORED LONGITUDINAL DATA AND SURVIVAL DATA WITH APPLICATION TO HIV VACCINE STUDIES

• 成果类型: Article
• 署名作者: Yu, Tingting; Wu, Lang; Qiu, Jin; Gilbert, Peter B.
• 署名单位: Harvard Pilgrim Health Care; Harvard University; Harvard Medical School; University of British Columbia; Zhejiang University of Finance & Economics; University of Washington; University of Washington Seattle
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/22-AOAS1656
• 发表日期: 2023
• 页码: 1017-1037
• 关键词: inference

摘要

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 longi-tudinal data are addressed using a multivariate t-distribution for b-outliers and using an M-estimator for e-outliers. We also propose a computationally effi-cient 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 lon-gitudinal biomarkers and the risk of HIV infection.