Survival Analysis

Abstract

In this chapter, the basic concepts and techniques of analyzing survival data are introduced. Different study designs for collecting survival data are discussed, and the corresponding procedures for estimating association between exposure and disease such as relative risk or odds ratio are discussed. Also, the procedures for constructing confidence intervals as well as for testing the hypothesis concerning any association between exposure and disease are highlighted for data from prospective, case-control, and cross-sectional study designs. The nonparametric methods of estimating survivor function are shown including the product-limit method . The variance of the estimator of survivor function is also obtained, and the log-rank test for comparing two survivor functions is also introduced in this chapter. One of the most widely used models in biostatistical data analysis is the logistic regression model which is introduced in this chapter with examples. The estimation and test procedures are discussed too. The basic concepts of longitudinal data analysis are discussed, and the proportional hazards model is introduced in this chapter with example. A simple method of model checking is also shown.