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140.641.01
Survival Analysis

Location:
East Baltimore
Term:
1st term
Department:
Biostatistics
Credits:
3 credits
Academic Year:
2019 - 2020
Class Times:
  • Tu Th,  3:30 - 4:50pm
Auditors Allowed:
Yes, with instructor consent
Grading Restriction:
Letter Grade or Pass/Fail
Course Instructor :
Contact:
Mei-Cheng Wang
Resources:
Prerequisite:

Biostatistics 140.611-2 or 140.651 or equivalent. Calculus I and II. Knowledge of fundamental probability and statistical theory is required.

Description:

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:

Upon successfully completing this course, students will be able to:

  1. Understand features of time-to-event data
  2. Explain fundamental concepts in survival analysis
  3. Describe statistical methods which are useful in medical follow-up studies and in general time-to-event studies
  4. Properly use software and packages to conduct time-to-event data analysis
Methods of Assessment:

This course is evaluated as follows:

  • 50% Homework
  • 50% Final Exam

Instructor Consent:

Consent required for some students

Consent Note:

Consent required for non-Biostatistics students

For consent, contact:

mcwang@jhu.edu

Special Comments:

Students must attend 2 one-hour lab sessions per week.