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ABSTRACT
This study introduces methods of analyzing data in survival analysis arising from studies where the response variable is the length of time taken to reach a certain end-point, and the aim of the study is to apply survival analysis with its application to life time data. The Kaplan-Meier methods, log rank test and Cox proportional hazards model are described, and was applied to a data set. Survival analysis provides special techniques that are required to compare the risks for death or other events associated with different treatments or groups, here the risk changes over time. In measuring survival time, the start and end-pints must be clearly defined and the censored observations noted. Kaplan- Meier provides a method for estimating the survival curve, the log rank test provides a statistical comparison of two groups, and Cox proportional hazards model allows additional covariates to be included. Both of the latter two methods assume that the hazard ratio comparing two groups is constant over time.
