Literature DB >> 1912255

Regression with frailty in survival analysis.

C A McGilchrist1, C W Aisbett.   

Abstract

In studies of survival, the hazard function for each individual may depend on observed risk variables but usually not all such variables are known or measurable. This unknown factor of the hazard function is usually termed the individual heterogeneity or frailty. When survival is time to the occurrence of a particular type of event and more than one such time may be obtained for each individual, frailty is a common factor among such recurrence times. A model including frailty is fitted to such repeated measures of recurrence times.

Mesh:

Year:  1991        PMID: 1912255

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  33 in total

1.  Using frailties in the accelerated failure time model.

Authors:  W Pan
Journal:  Lifetime Data Anal       Date:  2001-03       Impact factor: 1.588

2.  Fisher information for two gamma frailty bivariate Weibull models.

Authors:  H Bjarnason; P Hougaard
Journal:  Lifetime Data Anal       Date:  2000-03       Impact factor: 1.588

3.  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

4.  Semiparametric frailty models for clustered failure time data.

Authors:  Zhangsheng Yu; Xihong Lin; Wanzhu Tu
Journal:  Biometrics       Date:  2011-11-09       Impact factor: 2.571

5.  Modeling the effects of genetic factors on late-onset diseases in cohort studies.

Authors:  Mark E Glickman; David R Gagnon
Journal:  Lifetime Data Anal       Date:  2002-09       Impact factor: 1.588

6.  A class of parametric dynamic survival models.

Authors:  K Hemming; J E H Shaw
Journal:  Lifetime Data Anal       Date:  2005-03       Impact factor: 1.588

7.  Tests of independence for censored bivariate failure time data.

Authors:  Wenbin Lu
Journal:  Lifetime Data Anal       Date:  2007-03       Impact factor: 1.588

8.  A Weibull regression model with gamma frailties for multivariate survival data.

Authors:  S K Sahu; D K Dey; H Aslanidou; D Sinha
Journal:  Lifetime Data Anal       Date:  1997       Impact factor: 1.588

9.  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

10.  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

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