ST 475 - Survival Analysis and Generalized Linear Models

(3.00 cr.)

Consists of two parts. The first part provides a survey of the theory and application of survival analysis. Topics include time-to-event data, types of censoring, hazard functions, survival functions, Kaplan-Meier estimators, Nelson-Aalen estimators, and Cox proportional hazards models. Parametric methods and various nonparametric alternatives are discussed. The second part introduces the concepts and background of generalized linear models (GLMs). Topics include exponential family distributions, likelihood functions, link functions, simple and multiple linear regression, logistic regression for binary data, and Poisson regression for count data. Those methods are performed using statistical software - R and SAS.

Prerequisite: ST 310 .
Sessions Typically Offered: Fall
Years Typically Offered: Even Years

Interdisciplinary Studies: DS