Multiplicative rates model for recurrent events in case-cohort studies.

TitleMultiplicative rates model for recurrent events in case-cohort studies.
Publication TypeJournal Article
Year of Publication2020
AuthorsMaitra, Poulami, Leila D. A. F. Amorim, and Jianwen Cai
JournalLifetime Data Anal
Volume26
Issue1
Pagination134-157
Date Published2020 01
ISSN1572-9249
KeywordsCohort Studies, Computer Simulation, Humans, Prospective Studies, Recurrence, Regression Analysis
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.

DOI10.1007/s10985-019-09466-0
Alternate JournalLifetime Data Anal
Original PublicationMultiplicative rates model for recurrent events in case-cohort studies.
PubMed ID30734884
PubMed Central IDPMC6687570
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States
P30 ES010126 / ES / NIEHS NIH HHS / United States
Project: