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
Undergraduate Pre or Corequisite
[STAT4230 and STAT 4510/6510] or permission of department
Semester Course Offered
Offered spring
Grading System
A - F (Traditional)
Student learning Outcomes
Students will recognize survival data and identify various types of censoring and truncation, and apply basic tools of survival analysis.
Students will apply standard nonparametric and parametric statistical methods for analyzing failure-time data, including Kaplan–Meier estimation.
Students will conduct log-rank tests for comparing survival functions and perform regression analyses of failure-time data using proportional hazards and accelerated failure time models.
Students will conduct analyses of real-world data using statistical software and interpret the results of these 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
Methods of analysis including univariate parametric and nonparametric procedures, regression models, diagnostics, group comparisons
