Semiparametric regression with the U-shaped baseline hazard function in the additive hazards model under general censoring mechanisms

2021 ◽  
pp. 1-28
Author(s):  
Shabnam Fani ◽  
Hua Shen ◽  
Xuewen Lu ◽  
Jingjing Wu
Keyword(s):  
Hazard Function ◽  
Semiparametric Regression ◽  
Additive Hazards Model ◽  
Baseline Hazard ◽  
Additive Hazards ◽  
Baseline Hazard Function ◽  
Hazards Model

scholarly journals Review of Bayesian Analysis in Additive Hazards Model

2019 ◽  
pp. 1-14
Author(s):  
Alvarez, Enrique Ernesto ◽  
Riddick, Maximiliano Luis
Keyword(s):  
Hazard Function ◽  
Additive Model ◽  
Mcmc Methods ◽  
Additive Hazards Model ◽  
Previous Knowledge ◽  
Explanatory Variables ◽  
Bayesian Techniques ◽  
Additive Hazards ◽  
Hazards Model ◽  
Random Samples

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: \[ \lambda(t,z) := \lim_{\Delta \downarrow 0} \frac{P[T\leq t+ \Delta \vert T >t,Z=z]}{\Delta} .\] 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.

scholarly journals Regression Analysis of Additive Hazards Model With Latent Variables

2015 ◽  
Vol 110 (511) ◽  
pp. 1148-1159 ◽  
Author(s):  
Deng Pan ◽  
Haijin He ◽  
Xinyuan Song ◽  
Liuquan Sun
Keyword(s):  
Regression Analysis ◽  
Latent Variables ◽  
Additive Hazards Model ◽  
Additive Hazards ◽  
Hazards Model

Regression analysis of informative current status data with the additive hazards model

2014 ◽  
Vol 21 (2) ◽  
pp. 241-258 ◽  
Author(s):  
Shishun Zhao ◽  
Tao Hu ◽  
Ling Ma ◽  
Peijie Wang ◽  
Jianguo Sun
Keyword(s):  
Regression Analysis ◽  
Current Status Data ◽  
Current Status ◽  
Additive Hazards Model ◽  
Additive Hazards ◽  
Hazards Model ◽  
Status Data
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