scholarly journals Bayesian analysis of survival data with missing censoring indicators

Biometrics ◽  
2020 ◽  
Author(s):  
Naomi C. Brownstein ◽  
Veronica Bunn ◽  
Luis M. Castro ◽  
Debajyoti Sinha
Keyword(s):  
Bayesian Analysis ◽  
Survival Data ◽  
Missing Censoring Indicators

Bayesian Analysis of Survival Data with Semi-competing Risks and Treatment Switching

2013 ◽  
pp. 159-169
Author(s):  
Yuanye Zhang ◽  
Qingxia Chen ◽  
Ming-Hui Chen ◽  
Joseph G. Ibrahim ◽  
Donglin Zeng ◽  
...  
Keyword(s):  
Bayesian Analysis ◽  
Competing Risks ◽  
Survival Data ◽  
Treatment Switching

Semiparametric Bayesian Analysis of Survival Data

1997 ◽  
Vol 92 (439) ◽  
pp. 1195-1212 ◽  
Author(s):  
Debajyoti Sinha ◽  
Dipak K. Dey
Keyword(s):  
Bayesian Analysis ◽  
Survival Data

scholarly journals Bayesian Analysis of Topp-Leone Generalized Exponential Distribution

2018 ◽  
Vol 47 (4) ◽  
pp. 1-15
Author(s):  
Najrullah Khan ◽  
Athar Ali Khan
Keyword(s):  
Bayesian Analysis ◽  
Exponential Distribution ◽  
Bayesian Approach ◽  
Survival Data ◽  
Survival Model ◽  
Generalized Exponential Distribution ◽  
Data Set ◽  
Simulation Tools ◽  
Support Set ◽  
Optimization And Simulation

The Topp-Leone distribution was introduced by Topp-Leone in 1955. In this paper, an attempt has been made to fit Topp-Leone Generalized Exponential distribution. Since, Topp-Leone distribution contains only one parameter and its support set is restricted to (0,1), because of this, in most practical situations it is not a better fit for the lifetime modelling. So an extension of this distribution is required. A Bayesian approach has been adopted to fit this model as survival model. A real survival data set is used to illustrate. Implementation is done using R and JAGS and appropriate illustrations are made. R and JAGS codes have been provided to implement censoring mechanism using both optimization and simulation tools.

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