Literature DB >> 9160488

Marginal analysis of recurrent events and a terminating event.

R J Cook1, J F Lawless.   

Abstract

Chronic medical conditions are often manifested by the incidence of recurrent adverse clinical events. In clinical trials designed to investigate therapeutic interventions for such conditions it is natural to make treatment comparisons on the basis of event occurrence. However, when there is a more serious, possibly related, event that terminates the occurrence of the recurrent events, the problem of dependent censoring arises. Here, we consider robust modelling strategies for expressing covariate effects on the recurrent event process that address the possible dependence between the recurrent and terminal events. The various methods differ in the way the dependence is addressed, and hence in the interpretation of covariate effects. The methods are applied to a data set from a kidney transplant study and simulated data chosen for illustrative purposes.

Mesh:

Year:  1997        PMID: 9160488     DOI: 10.1002/(sici)1097-0258(19970430)16:8<911::aid-sim544>3.0.co;2-i

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  43 in total

1.  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

2.  Computationally efficient marginal models for clustered recurrent event data.

Authors:  Dandan Liu; Douglas E Schaubel; John D Kalbfleisch
Journal:  Biometrics       Date:  2011-09-29       Impact factor: 2.571

3.  Semiparametric regression for the weighted composite endpoint of recurrent and terminal events.

Authors:  Lu Mao; D Y Lin
Journal:  Biostatistics       Date:  2015-12-14       Impact factor: 5.899

4.  A semiparametric additive rates model for recurrent event data.

Authors:  Douglas E Schaubel; Donglin Zeng; Jianwen Cai
Journal:  Lifetime Data Anal       Date:  2006-09-20       Impact factor: 1.588

5.  A semiparametric additive rate model for recurrent events with an informative terminal event.

Authors:  Donglin Zeng; Jianwen Cai
Journal:  Biometrika       Date:  2010-07-26       Impact factor: 2.445

6.  A dynamic Mover-Stayer model for recurrent event processes subject to resolution.

Authors:  Hua Shen; Richard J Cook
Journal:  Lifetime Data Anal       Date:  2013-06-20       Impact factor: 1.588

7.  A flexible semiparametric transformation model for recurrent event data.

Authors:  Lin Dong; Liuquan Sun
Journal:  Lifetime Data Anal       Date:  2013-11-17       Impact factor: 1.588

8.  Semiparametric temporal process regression of survival-out-of-hospital.

Authors:  Tianyu Zhan; Douglas E Schaubel
Journal:  Lifetime Data Anal       Date:  2018-05-23       Impact factor: 1.588

9.  An estimating function approach to the analysis of recurrent and terminal events.

Authors:  John D Kalbfleisch; Douglas E Schaubel; Yining Ye; Qi Gong
Journal:  Biometrics       Date:  2013-05-07       Impact factor: 2.571

10.  Nonparametric Comparison for Multivariate Panel Count Data.

Authors:  Hui Zhao; Kate Virkler; Jianguo Sun
Journal:  Commun Stat Theory Methods       Date:  2014       Impact factor: 0.893

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