Review of Bayesian Analysis in Additive Hazards Model

In Survival Analysis, the focus of interest is a time T* until the occurrence of some event. A set of explanatory variables (denoted by a vector Z) is considered to analyze if there is a relationship between any of them and T*. Accordingly, the "hazard function" is defined: λ(t, z): = lim...

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Detalles Bibliográficos
Autores principales: Álvarez, Enrique Ernesto, Riddick, Maximiliano Luis
Formato: Articulo
Lenguaje:Inglés
Publicado: 2019
Materias:
Ciencias Exactas
Matemática
Survival analysis
Bayesian inference
Additive hazards model
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/128804
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-128804
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Exactas
Matemática
Survival analysis
Bayesian inference
Additive hazards model
spellingShingle Ciencias Exactas
Matemática
Survival analysis
Bayesian inference
Additive hazards model
Álvarez, Enrique Ernesto
Riddick, Maximiliano Luis
Review of Bayesian Analysis in Additive Hazards Model
topic_facet Ciencias Exactas
Matemática
Survival analysis
Bayesian inference
Additive hazards model
description In Survival Analysis, the focus of interest is a time T* until the occurrence of some event. A set of explanatory variables (denoted by a vector Z) is considered to analyze if there is a relationship between any of them and T*. Accordingly, the "hazard function" is defined: λ(t, z): = lim<sub>Δ↓0</sub> (P [T ≤ t + Δ | T > t, Z = z] / Δ) Several models are defined based on this, as is the case of the additive model (among others). Bayesian techniques allow to incorporate previous knowledge or presumption information about the parameters into the model. This area grows extensively since the computationally techniques increase, giving rise to powerful Markov Chain Monte Carlo (MCMC) methods, which allow to generate random samples from the desired distributions. The purpose of this article is to offer a summary of the research developed in Bayesian techniques to approach the additive hazard models.
format Articulo
Articulo
author Álvarez, Enrique Ernesto
Riddick, Maximiliano Luis
author_facet Álvarez, Enrique Ernesto
Riddick, Maximiliano Luis
author_sort Álvarez, Enrique Ernesto
title Review of Bayesian Analysis in Additive Hazards Model
title_short Review of Bayesian Analysis in Additive Hazards Model
title_full Review of Bayesian Analysis in Additive Hazards Model
title_fullStr Review of Bayesian Analysis in Additive Hazards Model
title_full_unstemmed Review of Bayesian Analysis in Additive Hazards Model
title_sort review of bayesian analysis in additive hazards model
publishDate 2019
url http://sedici.unlp.edu.ar/handle/10915/128804
work_keys_str_mv AT alvarezenriqueernesto reviewofbayesiananalysisinadditivehazardsmodel
AT riddickmaximilianoluis reviewofbayesiananalysisinadditivehazardsmodel
bdutipo_str Repositorios
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