Robust joint modelling of left-censored longitudinal data and survival data with application to HIV vaccine studies
Tingting Yu, Lang Wu, Jin Qiu, Peter B. Gilbert
The Annals of Applied Statistics · 2023 · Volume 17 · Issue 2
Abstract
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.
Keywords
biomarker, h-likelihood, left censoring, Outliers, robust joint model
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