Clegg L X, Cai J, Sen P K
National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892-7352, USA.
Biometrics. 1999 Sep;55(3):805-12. doi: 10.1111/j.0006-341x.1999.00805.x.
In multivariate failure time data analysis, a marginal regression modeling approach is often preferred to avoid assumptions on the dependence structure among correlated failure times. In this paper, a marginal mixed baseline hazards model is introduced. Estimating equations are proposed for the estimation of the marginal hazard ratio parameters. The proposed estimators are shown to be consistent and asymptotically Gaussian with a robust covariance matrix that can be consistently estimated. Simulation studies indicate the adequacy of the proposed methodology for practical sample sizes. The methodology is illustrated with a data set from the Framingham Heart Study.
在多变量失效时间数据分析中，通常更倾向于采用边际回归建模方法，以避免对相关失效时间之间的依赖结构做出假设。本文引入了一种边际混合基线风险模型。提出了用于估计边际风险比参数的估计方程。所提出的估计量被证明是一致的，并且渐近服从高斯分布，其协方差矩阵稳健且可一致估计。模拟研究表明，对于实际样本量，所提出的方法是充分的。用弗明汉心脏研究的一个数据集对该方法进行了说明。
