Survival Analysis On The Rate Of Diabetes Mellitus Patient Recovery With Bayesian Methode

Abstract

 In survival analysis, there is a survival model, the Cox model that used for knowing the risk factor, which influences the disease in time. Besides, the Cox model also used to determine the rate of recovery or the ability of somebody to survive from the disease. The model of regression Cox proportional hazard used for data where the assumption of proportional hazard has fulfilled. The estimation of regression cox model parameter, that is using the Bayesian method because the result will be more maximize than if we use the classic method. In this research, the Bayesian method applied in the case of diabetes mellitus patient in the public hospital of Dr. Saiful Anwar Malang from January to December 2015, that has 174 sample. Based on Credible Interval 2.50% and 97.50% known age is the significance of the independent variable. Meanwhile, the non-significant of independent variable which is the gender, employment status and others diagnose.