Alvares Danilo, Haneuse Sebastien, Lee Catherine, Lee Kyu Ha
Department of Statistics, Pontificia Universidad Católica de Chile, Macul, Santiago, Chile.
Department of Biostatistics, Harvard T. H. Chan School of Public Health, 02115 Boston, MA, USA.
R J. 2019 Jun;11(1):376-400. doi: 10.32614/rj-2019-038. Epub 2019 Aug 20.
Semi-competing risks refer to the setting where primary scientific interest lies in estimation and inference with respect to a non-terminal event, the occurrence of which is subject to a terminal event. In this paper, we present the R package that provides functions to perform the analysis of independent/clustered semi-competing risks data under the illness-death multi-state model. The package allows the user to choose the specification for model components from a range of options giving users substantial flexibility, including: accelerated failure time or proportional hazards regression models; parametric or non-parametric specifications for baseline survival functions; parametric or non-parametric specifications for random effects distributions when the data are cluster-correlated; and, a Markov or semi-Markov specification for terminal event following non-terminal event. While estimation is mainly performed within the Bayesian paradigm, the package also provides the maximum likelihood estimation for select parametric models. The package also includes functions for univariate survival analysis as complementary analysis tools.
半竞争风险是指主要科学兴趣在于对非终端事件进行估计和推断的情况,该非终端事件的发生受到终端事件的影响。在本文中,我们展示了一个R包,它提供了在疾病-死亡多状态模型下对独立/聚类半竞争风险数据进行分析的函数。该包允许用户从一系列选项中选择模型组件的规范,为用户提供了极大的灵活性,包括:加速失效时间或比例风险回归模型;基线生存函数的参数或非参数规范;当数据存在聚类相关性时,随机效应分布的参数或非参数规范;以及非终端事件之后终端事件的马尔可夫或半马尔可夫规范。虽然估计主要在贝叶斯范式内进行,但该包也为选定的参数模型提供了最大似然估计。该包还包括单变量生存分析函数作为补充分析工具。