ST 625 - W 25
Syllabus
Textbook:
Required: Modelling Survival Data in Medical Research, 4th Edition, Collett
Optional: Survival and Event History Analysis, Aalen, Borgan, and Gjessing
Optional: Counting Processes and Survival Analysis, Fleming and Harrington
Course objectives
To highlight the unique challenges posed by the analysis of failure/survival data. To allow you to analyze survival data using parametric and nonparametric techniques in the face of these challenges. To apply these techniques to real data using R code and R packages for survival analysis. To understand the theory and methodology through math, practice and code.
Course content
Concepts to be discussed include: hazard function (failure rate function); nonparametric likeli- hood; counting processes; empirical distribution function; censoring and truncation; Kaplan-Meier estimator; Bias of the KM estimator; Cox proportional hazards model; Accelerated Failure Time Model; Partial Likelihood; log-rank test; martingales. R will be the programming language used in the course.