Luo Sheng, Wang Jue
Division of Biostatistics, The University of Texas Health Science Center, Houston, 1200 Pressler St, Houston, TX 77030, U.S.A.
Stat Med. 2014 Oct 30;33(24):4279-91. doi: 10.1002/sim.6228. Epub 2014 Jun 17.
Multilevel item response theory models have been increasingly used to analyze the multivariate longitudinal data of mixed types (e.g., continuous and categorical) in clinical studies. To address the possible correlation between multivariate longitudinal measures and time to terminal events (e.g., death and dropout), joint models that consist of a multilevel item response theory submodel and a survival submodel have been previously developed. However, in multisite studies, multiple patients are recruited and treated by the same clinical site. There can be a significant site correlation because of common environmental and socioeconomic status, and similar quality of care within site. In this article, we develop and study several hierarchical joint models with the hazard of terminal events dependent on shared random effects from various levels. We conduct extensive simulation study to evaluate the performance of various models under different scenarios. The proposed hierarchical joint models are applied to the motivating deprenyl and tocopherol antioxidative therapy of Parkinsonism study to investigate the effect of tocopherol in slowing Parkinson's disease progression.
多级项目反应理论模型已越来越多地用于分析临床研究中混合类型（如连续型和分类型）的多变量纵向数据。为了解决多变量纵向测量与终末事件发生时间（如死亡和失访）之间可能存在的相关性，之前已开发出由多级项目反应理论子模型和生存子模型组成的联合模型。然而，在多中心研究中，多个患者由同一临床中心招募和治疗。由于共同的环境和社会经济状况以及中心内相似的医疗质量，可能存在显著的中心相关性。在本文中，我们开发并研究了几种层次联合模型，其中终末事件的风险取决于来自不同层次的共享随机效应。我们进行了广泛的模拟研究，以评估不同场景下各种模型的性能。所提出的层次联合模型应用于帕金森病的司来吉兰和维生素E抗氧化治疗的激励性研究，以研究维生素E在减缓帕金森病进展方面的作用。
