140.641.01 Survival Analysis
- 1st term
- 3 credits
- Academic Year:
- 2019 - 2020
- East Baltimore
- Class Times:
- Tu Th, 3:30 - 4:50pm
Introduces fundamental concepts, theory and methods in survival analysis. Emphasizes statistical tools and model interpretations which are useful in medical follow-up studies and in general time-to-event studies. Includes hazard functions, survival functions, types of censoring and truncation, Kaplan-Meier estimates, log-rank tests and their generalization. For parametric inference, includes likelihood estimation and the exponential, Weibull, log-logistic and other relevant distributions. Discusses in detail statistical methods and theory for the proportional hazard models (Cox model), with extensions to time-dependent covariates. Includes clinical and epidemiological examples (through class presentations). Illustrates various statistical procedures (through homework assignments).
- Learning Objectives:
- Understand features of time-to-event data
- Explain fundamental concepts in survival analysis
- Describe statistical methods which are useful in medical follow-up studies and in general time-to-event studies
- Properly use software and packages to conduct time-to-event data analysis
- Methods of Assessment:
Student evaluation based on homework problem sets, a final exam (including a closed book in class room part and a take-home data analysis part), and active course participation.
- Instructor Consent:
Consent required for some students
- Consent Note:
Consent required for non-Biostatistics students
- For consent, contact:
- Special Comments:
Students must attend 2 one-hour lab sessions per week.