Course Description
Methods for comparing time-to-event data, including univariate parametric and nonparametric procedures, regression models, diagnostics, group comparisons, and use of relevant statistical computing packages.
Additional Requirements for Graduate Students:
Extra homework problems will be assigned to graduate students, and graduate students will be required to submit a more complex final project than will undergraduates.
Athena Title
SURVIVAL ANALYSIS
Undergraduate Prerequisite
[(STAT 4210 or STAT 4110H) and STAT 4510/6510] or permission of department
Graduate Prerequisite
[(STAT 6220 or STAT 4230/6230 or STAT 6320 or STAT 6420 or BIOS 7020) and STAT 4510/6510] or permission of department
Semester Course Offered
Offered spring
Grading System
A - F (Traditional)
Course Objectives
Upon completion of the course, students will be able to recognize survival data and the various types of censoring and truncation that affect them. They will understand the basic tools of survival analysis and they will be able to implement standard nonparametric and parametric statistical methods for the analysis of failure time data, including Kaplan-Meier estimation and log-rank testing of survival functions and regression analysis of failure time data via proportional hazards models, logistic models and accelerated lifetime models. Students will be able to accomplish analyses of real data with these methods via statistical software and interpret the results of those analyses.
Topical Outline
Concepts and methods for the analysis of time-to-event data: basic tools for description of such data, concepts of censoring and truncation, and methods of analysis including univariate parametric and nonparametric procedures, regression models, diagnostics, group comparisons, and use of relevant statistical computing packages.