Literature DB >> 11280848

Using frailties in the accelerated failure time model.

W Pan1.   

Abstract

The accelerated failure time (AFT) model is an important alternative to the Cox proportional hazards model (PHM) in survival analysis. For multivariate failure time data we propose to use frailties to explicitly account for possible correlations (and heterogeneity) among failure times. An EM-like algorithm analogous to that in the frailty model for the Cox model is adapted. Through simulation it is shown that its performance compares favorably with that of the marginal independence approach. For illustration we reanalyze a real data set.

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Year:  2001        PMID: 11280848     DOI: 10.1023/a:1009625210191

Source DB:  PubMed          Journal:  Lifetime Data Anal        ISSN: 1380-7870            Impact factor:   1.588


  8 in total

1.  A linear mixed-effects model for multivariate censored data.

Authors:  W Pan; T A Louis
Journal:  Biometrics       Date:  2000-03       Impact factor: 2.571

2.  A multiple imputation approach to linear regression with clustered censored data.

Authors:  W Pan; J E Connett
Journal:  Lifetime Data Anal       Date:  2001-06       Impact factor: 1.588

3.  Semiparametric estimation of random effects using the Cox model based on the EM algorithm.

Authors:  J P Klein
Journal:  Biometrics       Date:  1992-09       Impact factor: 2.571

4.  The accelerated failure time model: a useful alternative to the Cox regression model in survival analysis.

Authors:  L J Wei
Journal:  Stat Med       Date:  1992 Oct-Nov       Impact factor: 2.373

5.  Regression with frailty in survival analysis.

Authors:  C A McGilchrist; C W Aisbett
Journal:  Biometrics       Date:  1991-06       Impact factor: 2.571

6.  Bivariate frailty model for the analysis of multivariate survival time.

Authors:  X Xue; R Brookmeyer
Journal:  Lifetime Data Anal       Date:  1996       Impact factor: 1.588

7.  A jackknife estimator of variance for Cox regression for correlated survival data.

Authors:  S R Lipsitz; M Parzen
Journal:  Biometrics       Date:  1996-03       Impact factor: 2.571

8.  The analysis of event history data: a review of progress and outstanding problems.

Authors:  D Clayton
Journal:  Stat Med       Date:  1988-08       Impact factor: 2.373

  8 in total
  5 in total

1.  Induced smoothing for the semiparametric accelerated failure time model: asymptotics and extensions to clustered data.

Authors:  Lynn M Johnson; Robert L Strawderman
Journal:  Biometrika       Date:  2009-06-25       Impact factor: 2.445

2.  Kernel Smoothed Profile Likelihood Estimation in the Accelerated Failure Time Frailty Model for Clustered Survival Data.

Authors:  Bo Liu; Wenbin Lu; Jiajia Zhang
Journal:  Biometrika       Date:  2013       Impact factor: 2.445

3.  Accelerated intensity frailty model for recurrent events data.

Authors:  Bo Liu; Wenbin Lu; Jiajia Zhang
Journal:  Biometrics       Date:  2014-03-03       Impact factor: 2.571

4.  A Semi-parametric Transformation Frailty Model for Semi-competing Risks Survival Data.

Authors:  Fei Jiang; Sebastien Haneuse
Journal:  Scand Stat Theory Appl       Date:  2016-08-31       Impact factor: 1.396

5.  An Accelerated Failure Time Cure Model with Shifted Gamma Frailty and Its Application to Epidemiological Research.

Authors:  Haro Aida; Kenichi Hayashi; Ayano Takeuchi; Daisuke Sugiyama; Tomonori Okamura
Journal:  Healthcare (Basel)       Date:  2022-07-25
  5 in total

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