This paper discusses regression analysis of a type of incomplete mixed data arising from event history studies with the proportional rates model. By mixed data, we mean that each study subject may be observed continuously during the whole study period, continuously over some study periods and at some time points, or only at some discrete time points. Therefore, we have combined recurrent event and panel count data. For the problem, we present a multiple imputation-based estimation procedure and one advantage of the proposed marginal model approach is that it can be easily implemented. To assess the performance of the procedure, a simulation study is conducted and indicates that it performs well for practical situations and can be more efficient than the existing method. The methodology is applied to a set of mixed data from a longitudinal cohort study.

中文翻译：

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使用比例比率模型对来自事件历史研究的不完整数据进行回归分析

本文讨论了使用比例模型对事件历史研究产生的一类不完全混合数据进行回归分析。混合数据是指每个研究对象可以在整个研究期间连续观察，在某些研究期间和某些时间点连续观察，或仅在某些离散时间点观察。因此，我们结合了经常性事件和面板计数数据。对于这个问题，我们提出了一种基于多重插补的估计过程，所提出的边际模型方法的一个优点是它可以很容易地实现。为了评估程序的性能，进行了一项模拟研究，表明它在实际情况下表现良好，并且比现有方法更有效。