Survival Analysis and Applications Using SAS and SPSS

Survival analysis is used to analyze data in which the time until the event is of interest. The event is sometimes, but not always, death. Typically, survival data is not completely observed. Instead, some of the data is censored. Censoring refers to missing data in a study before observing an event, such as subjects dropping out of trials or data that is otherwise lost. This chapter discusses the principles and applications of survival analysis using different events. Some of the major sections of this chapter include (1) the time-to-event data (survival data) and censored data, (2) the interpretation of the Kaplan–Meier curve and comparison of multiple curves, (3) the situation when it is appropriate to use different survival analysis methods, and (4) how to apply these concepts into the real-world case scenarios using SAS and SPSS.