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Published in: Lifetime Data Analysis 1/2020

08-02-2019

Multiplicative rates model for recurrent events in case-cohort studies

Authors: Poulami Maitra, Leila D. A. F. Amorim, Jianwen Cai

Published in: Lifetime Data Analysis | Issue 1/2020

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Abstract

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.

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Appendix
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Metadata
Title
Multiplicative rates model for recurrent events in case-cohort studies
Authors
Poulami Maitra
Leila D. A. F. Amorim
Jianwen Cai
Publication date
08-02-2019
Publisher
Springer US
Published in
Lifetime Data Analysis / Issue 1/2020
Print ISSN: 1380-7870
Electronic ISSN: 1572-9249
DOI
https://doi.org/10.1007/s10985-019-09466-0

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