A non-parametric test for independence of time to failure and cause of failure for discrete competing risks data

Statistics ◽  
2021 ◽  
pp. 1-16
Author(s):  
E. P. Sreedevi ◽  
Sudheesh K. Kattumannil ◽  
Isha Dewan
Keyword(s):  
Competing Risks ◽  
Time To Failure ◽  
Parametric Test ◽  
Competing Risks Data ◽  
Cause Of Failure ◽  
Non Parametric

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.

A simple non-parametric test for decreasing mean time to failure

2016 ◽  
Vol 60 (1) ◽  
pp. 73-87 ◽  
Author(s):  
Sudheesh K. Kattumannil ◽  
P. Anisha
Keyword(s):  
Time To Failure ◽  
Mean Time To Failure ◽  
Parametric Test ◽  
Mean Time ◽  
Non Parametric
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