Estimasi Model Shared Frailty Gamma dengan Maximum Hierarchical Likelihood (MHL) dalam Regresi Cox; Estimation Shared Gamma Frailty Model with Maximum Hierarchical Likelihood (MHL) in the Cox regression

Gultom, Idola S S, Danardono

2016 | Skripsi | FMIPA

Frailty models in survival analysis is an extension of the Cox regression, where this model can be seen through the elements of heterogeneity caused by explanatory variables are unobserved. The idea of the appearance of the model frailty (weakness) occurs in which individual must have different weaknesses (heterogeneous) so that it can be said that the most vulnerable individuals (frail) will die faster than other individuals. Cox regression or commonly known as proportional hazard models (proportional hazard model), where the value obtained from the hazard valued proportional hazard function, meaning covariates (explanatory variables) are comparable in effect or influence of an event. In this thesis, describes the parameter estimation procedure of the explanatory variables and the shared gamma frailty models using of maximum likelihood hierarchical method. By utilizing Breslow method to estimate the parameters beta and Newton Raphson algorithm, so as to simplify the estimation procedure.

Kata Kunci : : Survival analysis, Cox Regression, Maximum Hierarchical Likelihood, Model shared gamma Frailty, Newton Raphson.