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Analysis of bivariate recurrent event data with zero inflation

Authors
Kim, TaeunKim, Yang-Jin
Issue Date
Jan-2020
Publisher
KOREAN STATISTICAL SOC
Keywords
bivariate recurrent event; cure rate model; frailty effects; joint model; zero inflation
Citation
COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS, v.27, no.1, pp 37 - 46
Pages
10
Journal Title
COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS
Volume
27
Number
1
Start Page
37
End Page
46
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/146883
DOI
10.29220/CSAM.2020.27.1.037
ISSN
2287-7843
2383-4757
Abstract
Recurrent event data frequently occur in clinical studies, demography, engineering reliability and so on (Cook and Lawless, The Statistical Analysis of Recurrent Events, Springer, 2007). Sometimes, two or more different but related type of recurrent events may occur simultaneously. In this study, our interest is to estimate the covariate effect on bivariate recurrent event times with zero inflations. Such zero inflation can be related with susceptibility. In the context of bivariate recurrent event data, furthermore, such susceptibilities may be different according to the type of event. We propose a joint model including both two intensity functions and two cure rate functions. Bivariate frailty effects are adopted to model the correlation between recurrent events. Parameter estimates are obtained by maximizing the likelihood derived under a piecewise constant hazard assumption. According to simulation results, the proposed method brings unbiased estimates while the model ignoring cure rate models gives underestimated covariate effects and overestimated variance estimates. We apply the proposed method to a set of bivariate recurrent infection data in a study of child patients with leukemia.
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