Zeng Donglin, Cai Jianwen
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-7420, USA.
Lifetime Data Anal. 2005 Jun;11(2):151-74. doi: 10.1007/s10985-004-0381-0.
In biomedical studies, interest often focuses on the relationship between patient's characteristics or some risk factors and both quality of life and survival time of subjects under study. In this paper, we propose a simultaneous modelling of both quality of life and survival time using the observed covariates. Moreover, random effects are introduced into the simultaneous models to account for dependence between quality of life and survival time due to unobserved factors. EM algorithms are used to derive the point estimates for the parameters in the proposed model and profile likelihood function is used to estimate their variances. The asymptotic properties are established for our proposed estimators. Finally, simulation studies are conducted to examine the finite-sample properties of the proposed estimators and a liver transplantation data set is analyzed to illustrate our approaches.
在生物医学研究中，关注点通常集中在患者特征或某些风险因素与所研究对象的生活质量和生存时间之间的关系上。在本文中，我们提出使用观测到的协变量对生活质量和生存时间进行联合建模。此外，将随机效应引入联合模型，以考虑由于未观测因素导致的生活质量和生存时间之间的相关性。使用期望最大化（EM）算法来推导所提模型中参数的点估计，并使用轮廓似然函数来估计其方差。为我们提出的估计量建立了渐近性质。最后，进行模拟研究以检验所提估计量的有限样本性质，并分析一个肝移植数据集以说明我们的方法。
