Literature DB >> 35706984

Joint model for bivariate zero-inflated recurrent event data with terminal events.

Yang-Jin Kim1.   

Abstract

Bivariate recurrent event data are observed when subjects are at risk of experiencing two different type of recurrent events. In this paper, our interest is to suggest statistical model when there is a substantial portion of subjects not experiencing recurrent events but having a terminal event. In a context of recurrent event data, zero events can be related with either the risk free group or a terminal event. For simultaneously reflecting both a zero inflation and a terminal event in a context of bivariate recurrent event data, a joint model is implemented with bivariate frailty effects. Simulation studies are performed to evaluate the suggested models. Infection data from AML (acute myeloid leukemia) patients are analyzed as an application.
© 2020 Informa UK Limited, trading as Taylor & Francis Group.

Entities:  

Keywords:  Bivariate recurrent event; cure rate model; frailty effect; joint model; piecewise baseline; terminal event

Year:  2020        PMID: 35706984      PMCID: PMC9041912          DOI: 10.1080/02664763.2020.1744539

Source DB:  PubMed          Journal:  J Appl Stat        ISSN: 0266-4763            Impact factor:   1.416


  12 in total

1.  Nonparametric analysis of recurrent events and death.

Authors:  D Ghosh; D Y Lin
Journal:  Biometrics       Date:  2000-06       Impact factor: 2.571

2.  Cure frailty models for survival data: application to recurrences for breast cancer and to hospital readmissions for colorectal cancer.

Authors:  Virginie Rondeau; Emmanuel Schaffner; Fabien Corbière; Juan R Gonzalez; Simone Mathoulin-Pélissier
Journal:  Stat Methods Med Res       Date:  2011-06-01       Impact factor: 3.021

3.  Tests for multivariate recurrent events in the presence of a terminal event.

Authors:  Bingshu Eric Chen; Richard J Cook
Journal:  Biostatistics       Date:  2004-01       Impact factor: 5.899

4.  Marginal means/rates models for multiple type recurrent event data.

Authors:  Jianwen Cai; Douglas E Schaubel
Journal:  Lifetime Data Anal       Date:  2004-06       Impact factor: 1.588

5.  Shared frailty models for recurrent events and a terminal event.

Authors:  Lei Liu; Robert A Wolfe; Xuelin Huang
Journal:  Biometrics       Date:  2004-09       Impact factor: 2.571

6.  Joint frailty models for zero-inflated recurrent events in the presence of a terminal event.

Authors:  Lei Liu; Xuelin Huang; Alex Yaroshinsky; Janice N Cormier
Journal:  Biometrics       Date:  2015-08-21       Impact factor: 2.571

7.  Semiparametric analysis of correlated recurrent and terminal events.

Authors:  Yining Ye; John D Kalbfleisch; Douglas E Schaubel
Journal:  Biometrics       Date:  2007-03       Impact factor: 2.571

8.  Regression analysis of multivariate recurrent event data with a dependent terminal event.

Authors:  Liang Zhu; Jianguo Sun; Xingwei Tong; Deo Kumar Srivastava
Journal:  Lifetime Data Anal       Date:  2010-03-10       Impact factor: 1.588

9.  Estimation of intervention effects using recurrent event time data in the presence of event dependence and a cured fraction.

Authors:  Ying Xu; K F Lam; Yin Bun Cheung
Journal:  Stat Med       Date:  2014-01-22       Impact factor: 2.373

10.  Multi-state models for colon cancer recurrence and death with a cured fraction.

Authors:  A S C Conlon; J M G Taylor; D J Sargent
Journal:  Stat Med       Date:  2013-12-05       Impact factor: 2.373

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