School of Mathematics and Statistics, 12443Huazhong University of Science and Technology, Wuhan, China.
Department of Statistics, 26451The Chinese University of Hong Kong, Hong Kong, China.
Stat Methods Med Res. 2022 Jul;31(7):1292-1312. doi: 10.1177/09622802221089028. Epub 2022 Apr 4.
We propose a joint modeling approach to investigate the observed and latent risk factors of the multivariate failure times of interest. The proposed model comprises two parts. The first part is a distribution-free confirmatory factor analysis model that characterizes the latent factors by correlated multiple observed variables. The second part is a multivariate additive hazards model that assesses the observed and latent risk factors of the failure times. A hybrid procedure that combines the borrow-strength estimation approach and the asymptotically distribution-free generalized least square method is developed to estimate the model parameters. The asymptotic properties of the proposed estimators are derived. Simulation studies demonstrate that the proposed method performs well for practical settings. An application to a study concerning the risk factors of multiple diabetic complications is provided.
我们提出了一种联合建模方法，以研究多元失效时间的观测和潜在风险因素。所提出的模型由两部分组成。第一部分是一个无分布的确认性因素分析模型，通过相关的多个观测变量来描述潜在因素。第二部分是一个多元加性风险模型，评估失效时间的观测和潜在风险因素。开发了一种混合程序，将借强估计方法和渐近无分布广义最小二乘法结合起来，以估计模型参数。推导了所提出的估计量的渐近性质。模拟研究表明，该方法在实际情况下表现良好。提供了一个关于多种糖尿病并发症风险因素的研究的应用。
