Literature DB >> 25419022

A multiple imputation approach to the analysis of interval-censored failure time data with the additive hazards model.

Ling Chen1, Jianguo Sun2.   

Abstract

This paper discusses regression analysis of interval-censored failure time data, which occur in many fields including demographical, epidemiological, financial, medical, and sociological studies. For the problem, we focus on the situation where the survival time of interest can be described by the additive hazards model and a multiple imputation approach is presented for inference. A major advantage of the approach is its simplicity and it can be easily implemented by using the existing software packages for right-censored failure time data. Extensive simulation studies are conducted which indicate that the approach performs well for practical situations and is comparable to the existing methods. The methodology is applied to a set of interval-censored failure time data arising from an AIDS clinical trial.

Entities:  

Year:  2010        PMID: 25419022      PMCID: PMC4240511          DOI: 10.1016/j.csda.2009.10.022

Source DB:  PubMed          Journal:  Comput Stat Data Anal        ISSN: 0167-9473            Impact factor:   1.681


  8 in total

1.  A multiple imputation approach to Cox regression with interval-censored data.

Authors:  W Pan
Journal:  Biometrics       Date:  2000-03       Impact factor: 2.571

2.  Generalized additive models with interval-censored data and time-varying covariates: application to human immunodeficiency virus infection in hemophiliacs.

Authors:  Peter Bacchetti; Christopher Quale
Journal:  Biometrics       Date:  2002-06       Impact factor: 2.571

3.  Applications of multiple imputation to the analysis of censored regression data.

Authors:  G C Wei; M A Tanner
Journal:  Biometrics       Date:  1991-12       Impact factor: 2.571

4.  Hazard regression with interval-censored data.

Authors:  C Kooperberg; D B Clarkson
Journal:  Biometrics       Date:  1997-12       Impact factor: 2.571

5.  Regression analysis of interval-censored failure time data.

Authors:  J Sun
Journal:  Stat Med       Date:  1997-03-15       Impact factor: 2.373

6.  A proportional hazards model for interval-censored failure time data.

Authors:  D M Finkelstein
Journal:  Biometrics       Date:  1986-12       Impact factor: 2.571

Review 7.  Statistical methods in cancer research. Volume II--The design and analysis of cohort studies.

Authors:  N E Breslow; N E Day
Journal:  IARC Sci Publ       Date:  1987

8.  A proportional hazards model for multivariate interval-censored failure time data.

Authors:  W B Goggins; D M Finkelstein
Journal:  Biometrics       Date:  2000-09       Impact factor: 2.571

  8 in total
  3 in total

1.  Semiparametric regression analysis of partly interval-censored failure time data with application to an AIDS clinical trial.

Authors:  Qingning Zhou; Yanqing Sun; Peter B Gilbert
Journal:  Stat Med       Date:  2021-05-26       Impact factor: 2.373

2.  Regression analysis of incomplete data from event history studies with the proportional rates model.

Authors:  Guanglei Yu; Liang Zhu; Jianguo Sun; Leslie L Robison
Journal:  Stat Interface       Date:  2018       Impact factor: 0.716

3.  Multiple imputation strategies for a bounded outcome variable in a competing risks analysis.

Authors:  Elinor Curnow; Rachael A Hughes; Kate Birnie; Michael J Crowther; Margaret T May; Kate Tilling
Journal:  Stat Med       Date:  2021-01-19       Impact factor: 2.373

  3 in total

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