MODEL REGRESI COX PROPORSIONAL HAZARD PADA DATA KETAHANAN HIDUP

Abstract

A lot of events occured in daily life are connected with survival time, for example a time interval that measure the failure of a product, time duration which is needed to recover from disease, the back pain recurred after treatment. Data about survival time duration of an event is called survival data. Survival data can not be observed completely that is called as sensored data. Cox proportional hazard model is employed to analyze and determine the survival rate from cencored data affected one or more explanatory variables. This model assummed that the hazard rate of group is proportional to the hazard rate of another group. In the paper, wants to the factor that affect the survival of patient with cervical cancer. From the result of data processing that affect are age and stadum with cox proportionl hazard model is hi(t) = exp(-1.848U1i – 1.584U2i – 3.255S2i - 2.108S3i ) h0(t)