Literature DB >> 35706516

Estimation in the single change-point hazard function for interval-censored data with a cure fraction.

Bing Wang1, Xiaoguang Wang1, Lixin Song1.   

Abstract

In reliability or survival analysis, the hazard function plays a significant part for it can display the instantaneous failure rate at any time point. In practice, the abrupt change in hazard function at an unknown time point may occur after a maintenance activity or major operation. Under these circumstances, identifying the change point and estimating the size of the change are meaningful. In this paper, we assume that the hazard function is piecewise constant with a single jump at an unknown time. We propose the single change-point model for interval-censored survival data with a cure fraction. Estimation methods for the proposed model are investigated, and large-sample properties of the estimators are established. Simulation studies are carried out to evaluate the performance of the estimating method. The liver cancer data and breast cancer data are analyzed as the applications.
© 2019 Informa UK Limited, trading as Taylor & Francis Group.

Entities:  

Keywords:  Survival analysis; change-point hazard model; cure fraction; interval censoring; pseudo-maximum likelihood

Year:  2019        PMID: 35706516      PMCID: PMC9041630          DOI: 10.1080/02664763.2019.1635571

Source DB:  PubMed          Journal:  J Appl Stat        ISSN: 0266-4763            Impact factor:   1.416


  7 in total

1.  Variance estimation of a survival function for interval-censored survival data.

Authors:  J Sun
Journal:  Stat Med       Date:  2001-04-30       Impact factor: 2.373

2.  A nonparametric mixture model for cure rate estimation.

Authors:  Y Peng; K B Dear
Journal:  Biometrics       Date:  2000-03       Impact factor: 2.571

3.  Estimation of a change point in a hazard function based on censored data.

Authors:  Irène Gijbels; Ulkü Gürler
Journal:  Lifetime Data Anal       Date:  2003-12       Impact factor: 1.588

4.  A new estimation method for the semiparametric accelerated failure time mixture cure model.

Authors:  Jiajia Zhang; Yingwei Peng
Journal:  Stat Med       Date:  2007-07-20       Impact factor: 2.373

5.  Detecting multiple change points in piecewise constant hazard functions.

Authors:  Melody S Goodman; Yi Li; Ram C Tiwari
Journal:  J Appl Stat       Date:  2011-03-09       Impact factor: 1.404

6.  A semiparametric model for regression analysis of interval-censored failure time data.

Authors:  D M Finkelstein; R A Wolfe
Journal:  Biometrics       Date:  1985-12       Impact factor: 2.571

7.  On testing for a constant hazard against a change-point alternative.

Authors:  D E Matthews; V T Farewell
Journal:  Biometrics       Date:  1982-06       Impact factor: 2.571

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.