A joint model for mixed and truncated longitudinal data and survival data, with application to HIV vaccine studies.

ABSTRACT: In HIV vaccine studies, a major research objective is to identify immune response biomarkers measured longitudinally that may be associated with risk of HIV infection. This objective can be assessed via joint modeling of longitudinal and survival data. Joint models for HIV vaccine data are complicated by the following issues: (i) left truncations of some longitudinal data due to lower limits of quantification; (ii) mixed types of longitudinal variables; (iii) measurement errors and missing values in longitudinal measurements; (iv) computational challenges associated with likelihood inference. In this article, we propose a joint model of complex longitudinal and survival data and a computationally efficient method for approximate likelihood inference to address the foregoing issues simultan

SUBMITTER: Yu T 

PROVIDER: S-EPMC6193623 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature