Multiplicative rates model for recurrent events in case-cohort studies

  • Poulami Maitra
  • Leila D. A. F. Amorim
  • Jianwen CaiEmail author


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.


Generalized case-cohort design Recurrent events Correlated data Acute lower respiratory tract infections 



The authors thank the Editor, Associate Editor and reviewers for their helpful comments and suggestions that have improved the paper. This research was partially supported by grants from the National Institutes of Health (P01CA142538 and P30ES010126).


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Authors and Affiliations

  1. 1.Department of BiostatisticsUniversity of North Carolina at Chapel HillChapel HillUSA
  2. 2.Department of Statistics, Institute of MathematicsFederal University of BahiaSalvadorBrazil

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