Hu Xiangbin, Liu Li, Zhang Ying, Zhao Xingqiu
The Hong Kong Polytechnic University, Wuhan University and University of Nebraska Medical Center.
Stat Sin. 2023 Oct;33(4):2763-2786. doi: 10.5705/ss.202021.0213.
Informative terminal events often occur in the long term recurrent event follow-up studies. To reflect their effects on recurrent event processes explicitly, we propose a reversed nonparametric mean model for panel count data with a terminal event subject to right censoring. This model enjoys meaningful interpretation for applications and robustness for statistical inference. Treating the distribution of the right-censored terminal event time as a nuisance functional parameter, we develop a two-stage estimation procedure by combining the Kaplan-Meier estimator and nonparametric sieve estimation techniques. The consistency, convergence rate and asymptotic normality of the proposed nonparametric estimator are established. Then we construct a class of new statistics for two-sample test. The asymptotic properties of the new tests are established and evaluated by extensive simulation studies. Panel count data from Chinese Longitudinal Healthy Longevity study are analyzed using the proposed method for illustration.
信息性终末事件常在长期复发事件随访研究中出现。为明确反映它们对复发事件过程的影响，我们针对存在右删失终末事件的面板计数数据提出了一种反向非参数均值模型。该模型在应用方面具有有意义的解释，在统计推断方面具有稳健性。将右删失终末事件时间的分布视为一个干扰函数参数，我们通过结合Kaplan-Meier估计器和非参数筛估计技术，开发了一种两阶段估计程序。建立了所提出的非参数估计器的一致性、收敛速度和渐近正态性。然后我们构造了一类用于两样本检验的新统计量。通过广泛的模拟研究建立并评估了新检验的渐近性质。使用所提出的方法对中国健康与养老追踪调查（CLHLS）的面板计数数据进行了分析以作说明。
