Department of Biostatistics, Erasmus Medical Center, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands.
Stat Med. 2011 May 30;30(12):1366-80. doi: 10.1002/sim.4205. Epub 2011 Feb 21.
Motivated by a real data example on renal graft failure, we propose a new semiparametric multivariate joint model that relates multiple longitudinal outcomes to a time-to-event. To allow for greater flexibility, key components of the model are modelled nonparametrically. In particular, for the subject-specific longitudinal evolutions we use a spline-based approach, the baseline risk function is assumed piecewise constant, and the distribution of the latent terms is modelled using a Dirichlet Process prior formulation. Additionally, we discuss the choice of a suitable parameterization, from a practitioner's point of view, to relate the longitudinal process to the survival outcome. Specifically, we present three main families of parameterizations, discuss their features, and present tools to choose between them.
受肾脏移植物衰竭真实数据示例的启发，我们提出了一种新的半参数多维联合模型，将多个纵向结果与事件时间相关联。为了提供更大的灵活性，模型的关键组件采用非参数建模。具体来说，对于特定于主体的纵向演变，我们使用基于样条的方法，假设基线风险函数分段恒定，并且使用狄利克雷过程先验公式来对潜在项的分布进行建模。此外，我们还从实践者的角度讨论了选择合适的参数化方法，以将纵向过程与生存结果联系起来。具体来说，我们提出了三种主要的参数化方法族，讨论了它们的特点，并提供了在它们之间进行选择的工具。
