School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan, 430074, Hubei, People's Republic of China.
School of Science, East China University of Technology, Nanchang, 330013, Jiangxi, People's Republic of China.
Lifetime Data Anal. 2021 Apr;27(2):269-299. doi: 10.1007/s10985-020-09513-1. Epub 2021 Jan 8.
This paper deals with statistical inference procedure of multivariate failure time data when the primary covariate can be measured only on a subset of the full cohort but the auxiliary information is available. To improve efficiency of statistical inference, we use quadratic inference function approach to incorporate the intra-cluster correlation and use kernel smoothing technique to further utilize the auxiliary information. The proposed method is shown to be more efficient than those ignoring the intra-cluster correlation and auxiliary information and is easy to implement. In addition, we develop a chi-squared test for hypothesis testing of hazard ratio parameters. We evaluate the finite-sample performance of the proposed procedure via extensive simulation studies. The proposed approach is illustrated by analysis of a real data set from the study of left ventricular dysfunction.
本文研究了主要协变量仅在全队列的一个子集上可测量但辅助信息可用的多变量失效时间数据的统计推断方法。为了提高统计推断的效率，我们使用二次推断函数方法来纳入组内相关性，并使用核平滑技术进一步利用辅助信息。结果表明，与忽略组内相关性和辅助信息的方法相比，所提出的方法更有效，并且易于实现。此外，我们还开发了用于检验风险比参数的卡方检验。我们通过广泛的模拟研究评估了所提出程序的有限样本性能。通过对左心室功能障碍研究中真实数据集的分析来说明所提出的方法。
