Panel count data is common when the study subjects are exposed to recurrent events, observed only at discrete time points. In this article, we consider the regression analysis of panel count data with multiple modes of recurrence. We propose a proportional mean model to estimate the effect of covariates on the underlying counting process due to different modes of recurrence. The simultaneous estimation of baseline cumulative mean functions and regression parameters of $(k>1)$ recurrence modes are studied in detail. Asymptotic properties of the proposed estimators are also established. A Monte Carlo simulation study is carried out to validate the finite sample behaviour of the proposed estimators. The methods are applied to a real data arising from skin cancer chemoprevention trial.

翻译：当研究对象暴露于经常事件时,小组计数数据是常见的,只在离散的时间点观测到。在本条中,我们考虑了以多种重复模式对小组计数数据进行的回归分析。我们提出了一个比例平均模型,以估计由于不同重现模式而导致的共差对基本计数过程的影响。同时对基准累积平均函数和重现参数(k>1美元)进行详细研究。还确定了拟议估算者的非抽取性特性。进行了蒙特卡洛模拟研究,以验证拟议估算者的有限抽样行为。这些方法适用于皮肤癌预防实验产生的真实数据。