GS01 1023 Survival Analysis

Huang, Xuelin. Three semester hours. Spring, odd-numbered years. Grading System: Letter Grade. Prerequisite: Introduction to Biostatistics and Bioinformatics (GS010033) or permission of instructor.

Survival data are commonly encountered in scientific investigations, especially in clinical trials and epidemiologic studies.  In this course, commonly used statistical methods for the analysis of failure-time data will be discussed.  One of the primary topics is the estimation of survival function based on censored data, which include parametric failure-time models, and nonparametric Kaplan-Meier estimates of the survival distribution.  Estimation of the cumulative hazard function and the context of hypothesis testing for survival data will be covered.  These tests include the log rank test, generalized log-rank tests, and some non-ranked based test statistics.  Regression analysis for censored survival data is the most applicable to clinical trials and applied work.  The Cox proportional hazard mode, additive risk model, other alternative modeling techniques, and new theoretical and methodological advances in survival analysis will be discussed.