Literature DB >> 9160483

An overview of statistical methods for multiple failure time data in clinical trials.

L J Wei1, D V Glidden.   

Abstract

In a long term clinical trial to evaluate a new treatment, quite often each study subject may experience a number of 'failures' that correspond to repeated occurrences of the same type of event or events of entirely different natures during his/her follow-up period. To obtain efficient inference procedures for the therapeutic effect over time, it is desirable to utilize those multiple event times in the analysis. In this article, we review some useful procedures for analysing different kinds of multivariate failure time data. Specifically, we discuss the two-sample problems and the general regression problems with various survival models. We also give some recommendations of appropriate procedures for each type of multiple event data structure for practical usage.

Mesh:

Year:  1997        PMID: 9160483     DOI: 10.1002/(sici)1097-0258(19970430)16:8<833::aid-sim538>3.0.co;2-2

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


  27 in total

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3.  Linear signed-rank tests for paired survival data subject to a common censoring time.

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4.  Applied analysis of recurrent events: a practical overview.

Authors:  Jos W R Twisk; Nynke Smidt; Wieke de Vente
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5.  So many correlated tests, so little time! Rapid adjustment of P values for multiple correlated tests.

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6.  Current Methods for Recurrent Events Data with Dependent Termination: A Bayesian Perspective.

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Review 7.  Statistical Methods for Recurrent Event Analysis in Cohort Studies of CKD.

Authors:  Wei Yang; Christopher Jepson; Dawei Xie; Jason A Roy; Haochang Shou; Jesse Yenchih Hsu; Amanda Hyre Anderson; J Richard Landis; Jiang He; Harold I Feldman
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8.  Political factors affecting the enactment of state-level clean indoor air laws.

Authors:  Gregory Jackson Tung; Jon S Vernick; Elizabeth A Stuart; Daniel W Webster
Journal:  Am J Public Health       Date:  2014-04-17       Impact factor: 9.308

9.  Model comparisons of competing risk and recurrent events for graft failure in renal transplant recipients.

Authors:  Ingar Holme; Bengt C Fellström; Alan G Jardine; Anders Hartmann; Hallvard Holdaas
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10.  Semi-parametric risk prediction models for recurrent cardiovascular events in the LIPID study.

Authors:  Jisheng Cui; Andrew Forbes; Adrienne Kirby; Ian Marschner; John Simes; David Hunt; Malcolm West; Andrew Tonkin
Journal:  BMC Med Res Methodol       Date:  2010-04-01       Impact factor: 4.615

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