2025 Fall - Survival Analysis

This course aims to learn various statistical analysis approaches for dealing with time-to-event data, which is representative data we can see in biomedical area. After completing this course, you are expected to understand and explain followings:

• concept of censoring and survival time

• basic quantities for describing the distribution of survival data

• parametric methods for fitting the survival data

• nonparametric estimation methods

• semiparametric methods for regression problem

• use R/SAS to analyze survival data

• Lectures: Wed 13:00 - 15:50,   Mary's Hospital Annex (병원별관)  #1203

• Prerequisite: require at least 3rd year undergraduate students whose major is statistics

• prior exposure to basic statistics

•  probability and statistical inference

• linear regression

• exposure to the software language R

• Grading: (Tentatively) Homework (20%), Final project (30%), Exams (50%)

• There is no required textbook,  lecture notes will be provided

• Reference Books

  • Survival Analysis: Techniques for Censored and Truncated Data (2nd ed) by John P. Klein and Melvin L. Moeschberger

  • Survival Analysis: A Self-Learning Text (3rd ed) by  Kleinbaum, David G., Klein, Mitchel