Literature DB >> 20613974

Crossing Hazard Functions in Common Survival Models.

Jiajia Zhang1, Yingwei Peng.   

Abstract

Crossing hazard functions have extensive applications in modeling survival data. However, existing studies in the literature mainly focus on comparing crossed hazard functions and estimating the time at which the hazard functions cross, and there is little theoretical work on conditions under which hazard functions from a model will have a crossing. In this paper, we investigate crossing status of hazard functions from the proportional hazards (PH) model, the accelerated hazard (AH) model, and the accelerated failure time (AFT) model. We provide and prove conditions under which the hazard functions from the AH and the AFT models have no crossings or a single crossing. A few examples are also provided to demonstrate how the conditions can be used to determine crossing status of hazard functions from the three models.

Entities:  

Year:  2009        PMID: 20613974      PMCID: PMC2897182          DOI: 10.1016/j.spl.2009.07.002

Source DB:  PubMed          Journal:  Stat Probab Lett        ISSN: 0167-7152            Impact factor:   0.870


  3 in total

1.  Accelerated hazards regression model and its adequacy for censored survival data.

Authors:  Y Q Chen
Journal:  Biometrics       Date:  2001-09       Impact factor: 2.571

2.  Comparing two crossing hazard rates by Cox proportional hazards modelling.

Authors:  Kejian Liu; Peihua Qiu; Jun Sheng
Journal:  Stat Med       Date:  2007-01-30       Impact factor: 2.373

3.  Hazard rate estimation under random censoring with varying kernels and bandwidths.

Authors:  H G Müller; J L Wang
Journal:  Biometrics       Date:  1994-03       Impact factor: 2.571

  3 in total
  3 in total

1.  A New Semiparametric Estimation Method for Accelerated Hazards Mixture Cure Model.

Authors:  Jiajia Zhang; Yingwei Peng; Haifen Li
Journal:  Comput Stat Data Anal       Date:  2013-03       Impact factor: 1.681

2.  Induced Smoothing for the Semiparametric Accelerated Hazards Model.

Authors:  Haifen Li; Jiajia Zhang; Yincai Tang
Journal:  Comput Stat Data Anal       Date:  2012-04-09       Impact factor: 1.681

3.  Bayes factors for choosing among six common survival models.

Authors:  Jiajia Zhang; Timothy Hanson; Haiming Zhou
Journal:  Lifetime Data Anal       Date:  2018-03-30       Impact factor: 1.588

  3 in total

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