In large prospective cohort studies, accumulation of covariate information and follow-up data make up the majority of the cost involved in the study. This might lead to the study being infeasible when there are some expensive variables and/or the event is rare. Prentice (Biometrika 73(1):1–11, 1986) proposed the case-cohort study for time to event data to tackle this problem. There has been extensive research on the analysis of univariate and clustered failure time data, where the clusters are formed among different individuals under case-cohort sampling scheme. However, recurrent event data are quite common in biomedical and public health research. In this paper, we propose case-cohort sampling schemes for recurrent events. We consider a multiplicative rates model for the recurrent events and propose a weighted estimating equations approach for parameter estimation. We show that the estimators are consistent and asymptotically normally distributed. The proposed estimator performed well in finite samples in our simulation studies. For illustration purposes, we examined the association between prior occurrence of measles on acute lower respiratory tract infections (ALRI) among young children in Brazil.

中文翻译：

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病例组研究中复发事件的乘法率模型。

在大型前瞻性队列研究中，协变量信息和后续数据的积累构成了研究成本的大部分。当存在一些昂贵的变量和/或事件很少发生时，这可能导致该研究不可行。Prentice（Biometrika 73（1）：1-11，1986）提出了案例研究，以获取事件发生时间的数据来解决这个问题。对于单变量和聚类的故障时间数据的分析已经进行了广泛的研究，其中在案例队列抽样方案下，不同个体之间形成了聚类。但是，复发事件数据在生物医学和公共卫生研究中非常普遍。在本文中，我们提出了针对复发事件的病例队列抽样方案。我们考虑周期性事件的乘数率模型，并提出用于参数估计的加权估计方程方法。我们表明估计量是一致的并且渐近正态分布。在我们的模拟研究中，建议的估计器在有限样本中表现良好。为了说明的目的，我们检查了巴西幼儿中先前发生的急性下呼吸道感染（ALRI）麻疹之间的关联。