MODEL REGRESSION COX PROPORTIONAL HAZARD WITH BAYESIAN METHOD FOR SURVIVAL ANALYSIS OF COVID-19 PATIENT CASES AT RSUD Dr. PIRNGADI KOTA MEDAN - Anandara, Aurelia; Nasution, Hamidah; Husein, Ismail (UIN Sumatera Utara, 2022)
Survival analysis is a statistical procedure for analyzing data by observing the response variable in the form of event time data from the beginning of recording to the end of the event. Survival analysis is used in many fields of medicine. The cox proportional hazard model aims to look at the factors of the recovery rate on patient survival. In this study using Bayesian data with Lognormal distribution in Covid-19 patients at Dr. Pirngadi, Medan City. The predictor variables are Age, gender, employment status, and other diagnose. Based on the research, the cox proportional hazard model was obtained with the influential variables based on the credible interval it is known that the age and genderare significant variables. Among the two variables that have the most influence is the age because it obtains a larger coefficient, namely