Bayesian sensitivity analysis to the non-ignorable missing cause of failure for hybrid censored competing risks data

2020 ◽  
Vol 90 (12) ◽  
pp. 2228-2255
Author(s):  
Fariba Azizi ◽  
Samaneh Eftekhari Mahabadi ◽  
Elham Mosayebi Omshi
Keyword(s):  
Sensitivity Analysis ◽  
Competing Risks ◽  
Competing Risks Data ◽  
Cause Of Failure ◽  
Missing Cause Of Failure

Modelling competing risks data with missing cause of failure

2010 ◽  
Vol 29 (30) ◽  
pp. 3172-3185 ◽  
Author(s):  
Giorgos Bakoyannis ◽  
Fotios Siannis ◽  
Giota Touloumi
Keyword(s):  
Competing Risks ◽  
Competing Risks Data ◽  
Cause Of Failure ◽  
Missing Cause Of Failure

scholarly journals Regression Analysis of Masked Competing Risks Data under Cumulative Incidence Function Framework

2020 ◽  
Vol 49 (3) ◽  
pp. 25-29
Author(s):  
Yosra Yousif ◽  
Faiz Ahmed Mohamed Elfaki ◽  
Meftah Hrairi
Keyword(s):  
Competing Risks ◽  
Cumulative Incidence ◽  
Model Simulation ◽  
Cumulative Incidence Function ◽  
Subdistribution Hazard ◽  
Incidence Function ◽  
Proposed Model ◽  
Competing Risks Data ◽  
Cause Of Failure ◽  
Proportional Subdistribution Hazard

In the studies that involve competing risks, somehow, masking issues might arise. That is, the cause of failure for some subjects is only known as a subset of possible causes. In this study, a Bayesian analysis is developed to assess the effect of risks factor on the Cumulative Incidence Function (CIF) by adopting the proportional subdistribution hazard model. Simulation is conducted to evaluate the performance of the proposed model and it shows that the model is feasible for the possible applications.

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