Abstract
This chapter introduces some commonly used statistical methods for survival time data in medical research. The chapter describes features of survival time data, defines the survival function, and introduces the product-limit estimator for the survival function. Finally, a summary of stratified analysis and Cox's regression analysis are described. The problem of analyzing survival time data is complicated, because the follow-up length is often different for each participant and the event of interest. For survival analysis, main interest focuses on the time taken for some dichotomous event to occur. The stratified logrank test is a useful method for comparing the survival between two treatment groups while accounting for the effects of prognostic factors. The regression coefficients are usually unknown and need to be estimated from the data. It is complex to estimate these regression coefficients. When the sample size is large, the estimate of each regression coefficient follows a normal distribution approximately.
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