Literature DB >> 21076872

Destructive weighted Poisson cure rate models.

Josemar Rodrigues1, Mário de Castro, N Balakrishnan, Vicente G Cancho.   

Abstract

In this paper, we develop a flexible cure rate survival model by assuming the number of competing causes of the event of interest to follow a compound weighted Poisson distribution. This model is more flexible in terms of dispersion than the promotion time cure model. Moreover, it gives an interesting and realistic interpretation of the biological mechanism of the occurrence of event of interest as it includes a destructive process of the initial risk factors in a competitive scenario. In other words, what is recorded is only from the undamaged portion of the original number of risk factors.

Mesh:

Year:  2010        PMID: 21076872     DOI: 10.1007/s10985-010-9189-2

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


  4 in total

1.  Estimating Cure Rates From Survival Data: An Alternative to Two-Component Mixture Models.

Authors:  A D Tsodikov; J G Ibrahim; A Y Yakovlev
Journal:  J Am Stat Assoc       Date:  2003-12-01       Impact factor: 5.033

2.  Application of the promotion time cure model with time-changing exposure to the study of HIV/AIDS and other infectious diseases.

Authors:  M Tournoud; R Ecochard
Journal:  Stat Med       Date:  2007-02-28       Impact factor: 2.373

3.  A stochastic two-stage carcinogenesis model: a new approach to computing the probability of observing tumor in animal bioassays.

Authors:  G L Yang; C W Chen
Journal:  Math Biosci       Date:  1991-05       Impact factor: 2.144

4.  A stochastic model of radiation carcinogenesis: latent time distributions and their properties.

Authors:  L B Klebanov; S T Rachev
Journal:  Math Biosci       Date:  1993-01       Impact factor: 2.144

  4 in total
  1 in total

1.  Stochastic EM algorithm for generalized exponential cure rate model and an empirical study.

Authors:  Katherine Davies; Suvra Pal; Joynob A Siddiqua
Journal:  J Appl Stat       Date:  2020-06-30       Impact factor: 1.416

  1 in total

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