Methods of the Survival Analysis

The survival analysis is a set of statistical methods dealing with time-to-event data. In biomedical applications the event of interest is usually relapse of the disease or death. A special feature of the survival analysis is censoring and truncation of data. When censoring or truncation occurs some information about the patients' survival is lost, e.g. some patients are lost to follow-up or the study ends before all the patients die. The survival analysis methods are used for estimation of the survival time distribution, for identification of risk factors that affect the survival time, and also for predicting the survival time when risk factors are present. Survival analysis methods have been further developed by the means of counting processes and martingale theory. Univariate survival analysis methods have been extended to multivariate setting. The multivariate survival analysis covers the field where independence between survival times cannot be assumed. Multi-state models and frailty models represent the two main approaches of multivariate methods