北京师范大学童行伟教授“混合经常性事件和面板计数数据回归分析”大意为：在涉及复发事件事件历史研究中，两种类型的数据都得到了广泛的讨论。一个是复发事件数据。另一种是面板计数数据。在前者的情况下，所有的研究对象被连续监测;因此，完整的信息，请感兴趣的潜在的经常性事件的过程。在后一种情况下，研究对象是周期性监测;因此，仅不完全信息可用于所关注的进程。然而在现实中，第三类型的数据可能发生在其中的一些研究受试者连续监测，但是其他定期监测。如果发生这种情况，我们已混合复发事件和面板计数数据。本文探讨了这种混合数据回归分析，并提出两种估计方法的问题。一个是最大似然估计程序，而另一个是一个估计方程的过程。两者产生的回归参数估计的渐近性质确定。此外，方法应用于一组混合复发事件和面板计数的数据，从一个儿童癌症幸存者研究起来，促使本次调查。以下为原文。

　　Regression analysis of mixed recurrent-event and panel-count data

　　In event history studies concerning recurrent events, two types of data have been extensively discussed. One is recurrent-event data (Cook and Lawless, 2007), and the other is panel-count data (Zhao et al., 2010). In the former case, all study subjects are monitored continuously; thus, complete information is available for the underlying recurrent-event processes of interest. In the latter case, study subjects are monitored periodically; thus, only incomplete information is available for the processes of interest. In reality, however, a third type of data could occur in which some study subjects are monitored continuously, but others are monitored periodically. When this occurs, we have mixed recurrent-event and panel-count data. This paper discusses regression analysis of such mixed data and presents two estimation procedures for the problem. One is a maximum likelihood estimation procedure, and the other is an estimating equation procedure. The asymptotic properties of both resulting estimators of regression parameters are established. Also, the methods are applied to a set of mixed recurrent-event and panel-count data that arose from a Childhood Cancer Survivor Study and motivated this investigation