TY - JOUR
T1 - Use of Frailty Propertional Risk Rate Model in Real Data Analysis
TT - استفاده از مدل بی ثبات نرخ خطر متناسب در تحلیل داده های واقعی
JF - Andishe-_ye-Amari
JO - Andishe-_ye-Amari
VL - 25
IS - 1
UR - http://andisheyeamari.irstat.ir/article-1-790-en.html
Y1 - 2021
SP - 25
EP - 31
KW - Likelihood Maximum Estimator
KW - Baseline Distribution
KW - Unconditional Survival Functions
KW - Frailty Model .
N2 - Many populations encountered in survival analysis are often not homogeneous. Individuals are flexible in their susceptibility to causes of death, response to treatment, and influence of various risk factors. Ignoring this heterogeneity can result in misleading conclusions. To deal with these problems, the proportional hazard frailty model was introduced. In this paper, the frailty model is explained as the product of the frailty random variable and baseline hazard rate. We examine the fit of the frailty model to the right-censored data from in the presence of explanatory variables (observable variables) and use it as a practical example to fit the frailty model to the data by considering the Weibull basis distribution and exponential in the likelihood functions. It is used to estimate the model parameters and compare the fit of the models with different criteria.
M3
ER -