ABSTRACT
Estimation of time to event is an important aspect in scientific research. It could be the time to release a film, time to get a cadaver organ, time to failure of a machine etc. This is like a waiting time and depends on several factors and in health studies, this is known as survival time with death as the event of interest. The pattern of happening of such events is known as hazard rate.
This chapter presents the concept and practical application of two important tools of survival analysis. The first one is the Kaplan-Meier method to estimate the mean/median survival time and to compare the survival pattern between two treatment groups. The second and more general one is the Cox Regression (proportional hazard model) which is used when more than one factor show impact on the survival pattern. The outline of data setup, the inputs to be supplied for analysis and the interpretation of output particularly the relative risk (of event) are discussed in a lucid manner with the help of real datasets. (176)
