Literature DB >> 27339474

Association measures for bivariate failure times in the presence of a cure fraction.

Lajmi Lakhal-Chaieb1, Thierry Duchesne2.   

Abstract

This paper proposes a new joint model for pairs of failure times in the presence of a cure fraction. The proposed model relaxes some of the assumptions required by the existing approaches. This allows us to add some flexibility to the dependence structure and to widen the range of association measures that can be defined. A numerically stable iterative algorithm based on estimating equations is proposed to estimate the parameters. The estimators are shown to be consistent and asymptotically normal. Simulations show that they have good finite-sample properties. The added flexibility of the proposal is illustrated with an application to data from a diabetes retinopathy study.

Entities:  

Keywords:  Association measure; Copula; ES-algorithm; Kendall’s tau; Linear transformation model

Mesh:

Year:  2016        PMID: 27339474     DOI: 10.1007/s10985-016-9371-2

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


  14 in total

1.  A bivariate cure-mixture approach for modeling familial association in diseases.

Authors:  N Chatterjee; J Shih
Journal:  Biometrics       Date:  2001-09       Impact factor: 2.571

2.  A bivariate frailty model with a cure fraction for modeling familial correlations in diseases.

Authors:  Andreas Wienke; Paul Lichtenstein; Anatoli I Yashin
Journal:  Biometrics       Date:  2003-12       Impact factor: 2.571

3.  Modelling paired survival data with covariates.

Authors:  W J Huster; R Brookmeyer; S G Self
Journal:  Biometrics       Date:  1989-03       Impact factor: 2.571

4.  Parametric versus non-parametric methods for estimating cure rates based on censored survival data.

Authors:  A B Cantor; J J Shuster
Journal:  Stat Med       Date:  1992-05       Impact factor: 2.373

5.  Local linear estimation of concordance probability with application to covariate effects models on association for bivariate failure-time data.

Authors:  Aidong Adam Ding; Jin-Jian Hsieh; Weijing Wang
Journal:  Lifetime Data Anal       Date:  2013-12-10       Impact factor: 1.588

6.  Time-dependent cross ratio estimation for bivariate failure times.

Authors:  Tianle Hu; Bin Nan; Xihong Lin; James M Robins
Journal:  Biometrika       Date:  2011-06       Impact factor: 2.445

7.  Parametric versus non-parametric methods for estimating cure rates based on censored survival data.

Authors:  Y u Yakovlev A
Journal:  Stat Med       Date:  1994-05-15       Impact factor: 2.373

8.  Mixture cure model with random effects for the analysis of a multi-center tonsil cancer study.

Authors:  Yingwei Peng; Jeremy M G Taylor
Journal:  Stat Med       Date:  2010-11-05       Impact factor: 2.373

Review 9.  Prevalence of diabetic retinopathy in various ethnic groups: a worldwide perspective.

Authors:  Sobha Sivaprasad; Bhaskar Gupta; Roxanne Crosby-Nwaobi; Jennifer Evans
Journal:  Surv Ophthalmol       Date:  2012-04-28       Impact factor: 6.048

10.  Semiparametric Maximum Likelihood Estimation in Normal Transformation Models for Bivariate Survival Data.

Authors:  Yi Li; Ross L Prentice; Xihong Lin
Journal:  Biometrika       Date:  2008-12       Impact factor: 2.445

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