PENDEKATAN MODEL COMPETING RISK DENGAN HAZARD CUMULATIVE INCIDENCE FUNCTION (CIF); COMPETING RISK MODEL APPROACH WITH HAZARD CUMULATIVE INCIDENCE FUNCTION (CIF)

Alfauzani, Nisaul Aufa, Danardono

2015 | Skripsi | FMIPA UGM

Time-to-event data is time length data until the event occurs. Some situations is not appropriate in the ordinary survival method application. One of the situations is the competing risk event. Generally, It occurs when an individual can face more than one type of events, and this event precludes the occurrence of another event. The times of event in the competing risk is effected by other independent variables (covariat). The analysis used is hazard regression analysis of Cumulative Incidence Function (CIF). In competing risk model, regression coefficients is fixed and the value does not depend on the time. The method used for estimate regression coefficients is maximum partial likelihood method similar with in Cox regression model. In this paper, CIF hazard analysis regression with competing risk model is used to analyze some variables that affect time the leukemia patient death after bone marrow transplantation because one of causes type the patient death, that treated in European Society for Blood and Marrow Transplantation (EBMT). It is also presented that the CIF graphics used to interpret the affect from each independent variables and used to know the largest risk for every causes. Keywords: time-to-event data, survival function, hazard function, competing risk, maximum partial likelihood, Cumulative Incidence Function (CIF), Cox regression

Kata Kunci : Competing Risk Model Approach; Cumulative Incidence Function