Literature DB >> 24999008

Weighted comparison of two cumulative incidence functions with R-CIFsmry package.

Jianing Li1, Jennifer Le-Rademacher2, Mei-Jie Zhang1.   

Abstract

In this paper we propose a class of flexible weight functions for use in comparison of two cumulative incidence functions. The proposed weights allow the users to focus their comparison on an early or a late time period post treatment or to treat all time points with equal emphasis. These weight functions can be used to compare two cumulative incidence functions via their risk difference, their relative risk, or their odds ratio. The proposed method has been implemented in the R-CIFsmry package which is readily available for download and is easy to use as illustrated in the example.
Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Competing risks; Cumulative incidence functions; Risk difference; Weighted comparison

Mesh:

Year:  2014        PMID: 24999008      PMCID: PMC4285697          DOI: 10.1016/j.cmpb.2014.05.008

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  9 in total

1.  Regression modeling of competing risks data based on pseudovalues of the cumulative incidence function.

Authors:  John P Klein; Per Kragh Andersen
Journal:  Biometrics       Date:  2005-03       Impact factor: 2.571

2.  Modeling cumulative incidence function for competing risks data.

Authors:  Mei-Jie Zhang; Xu Zhang; Thomas H Scheike
Journal:  Expert Rev Clin Pharmacol       Date:  2008-05-01       Impact factor: 5.045

3.  Prediction of cumulative incidence function under the proportional hazards model.

Authors:  S C Cheng; J P Fine; L J Wei
Journal:  Biometrics       Date:  1998-03       Impact factor: 2.571

4.  Non-parametric inference for cumulative incidence functions in competing risks studies.

Authors:  D Y Lin
Journal:  Stat Med       Date:  1997-04-30       Impact factor: 2.373

5.  The analysis of failure times in the presence of competing risks.

Authors:  R L Prentice; J D Kalbfleisch; A V Peterson; N Flournoy; V T Farewell; N E Breslow
Journal:  Biometrics       Date:  1978-12       Impact factor: 2.571

6.  Analyzing Competing Risk Data Using the R timereg Package.

Authors:  Thomas H Scheike; Mei-Jie Zhang
Journal:  J Stat Softw       Date:  2011-01       Impact factor: 6.440

7.  Summarizing differences in cumulative incidence functions.

Authors:  Mei-Jie Zhang; Jason Fine
Journal:  Stat Med       Date:  2008-10-30       Impact factor: 2.373

8.  Bone marrow transplantation from HLA-identical siblings as treatment for myelodysplasia.

Authors:  Jorge Sierra; Waleska S Pérez; Ciril Rozman; Enric Carreras; John P Klein; J Douglas Rizzo; Stella M Davies; Hillard M Lazarus; Christopher N Bredeson; David I Marks; Carmen Canals; Marc A Boogaerts; John Goldman; Richard E Champlin; Armand Keating; Daniel J Weisdorf; Theo M de Witte; Mary M Horowitz
Journal:  Blood       Date:  2002-09-15       Impact factor: 22.113

9.  Flexible competing risks regression modeling and goodness-of-fit.

Authors:  Thomas H Scheike; Mei-Jie Zhang
Journal:  Lifetime Data Anal       Date:  2008-08-28       Impact factor: 1.588

  9 in total
  2 in total

1.  Implementation of an Alternative Method for Assessing Competing Risks: Restricted Mean Time Lost.

Authors:  Hongji Wu; Hao Yuan; Zijing Yang; Yawen Hou; Zheng Chen
Journal:  Am J Epidemiol       Date:  2022-01-01       Impact factor: 5.363

2.  Risk Factors and Incidence of Epilepsy after Severe Traumatic Brain Injury.

Authors:  Matthew Pease; Jorge Gonzalez-Martinez; Ava Puccio; Enyinna Nwachuku; James F Castellano; David O Okonkwo; Jonathan Elmer
Journal:  Ann Neurol       Date:  2022-08-03       Impact factor: 11.274

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.