scholarly journals Asymptotic theory for the correlated gamma-frailty model

1998 ◽  
Vol 26 (1) ◽  
pp. 183-214 ◽  
Author(s):  
Erik Parner
Biostatistics ◽  
2008 ◽  
Vol 10 (1) ◽  
pp. 187-200 ◽  
Author(s):  
M. A. Jonker ◽  
S. Bhulai ◽  
D. I. Boomsma ◽  
R. S. L. Ligthart ◽  
D. Posthuma ◽  
...  

2005 ◽  
Vol 11 (2) ◽  
pp. 265-284 ◽  
Author(s):  
Peter Barker ◽  
Robin Henderson

2020 ◽  
Vol 21 (1) ◽  
pp. 187-200
Author(s):  
Arvind Pandey ◽  
Shashi Bhushan ◽  
Lalpawimawha Ralte
Keyword(s):  

Author(s):  
Catherine Rexy D ◽  
Mokesh Rayalu G ◽  
Ponnuraja C

A natural of survival analysis associated the modelling of time-to-failure, consider the time until death or failure. The frailty model could be a random effect unobserved information, wherever the random effect an increasing, impact of baseline hazard function. The frailty model provides a convenient way to introduce random effects, accounts for further variability from unobserved factors, and heterogeneity into models for survival information. This text planned to analyze the frailty gamma distribution has been active to the parameter distribution acting as Weibull, log logistic and log normal distributions with a naturally incidental variable so as to diagnose the prognostic cause that effect the infectious disease patients for survival time. Information analysis is performed victimization STATA software package. Keyword: Frailty model; Parametric Distribution; Gamma frailty model -2LL; Tuberculosis Patients


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