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GS01 1023 Survival Analysis

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

Survival data are commonly encountered in scientific investigations, especially in clinical trials and epidemiologic studies. In this course, we will discuss commonly used statistical methods for the analysis of failure-time data. 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 estimate of the survival distribution. We will also discuss estimation of the cumulative hazard function. Moreover, we will cover the context of hypothesis testing for survival data. These test include the log rank test, generalized log-rank tests, and some non-rank based test statistics. The most applicable to clinical trials and applied work is regression analysis for censored survival data. We will include the Cox proportional hazard model, additive risk model and other alternative modeling techniques. Finally, we will also discuss a number of new theoretical and methodological advances in survival analysis.