140.641.01 | AY 2013-2014 - 1st Term | 3 Credit(s)
TTh 3:30:00 PM
  • Contact Information
    Mei-Cheng Wang
  • Course Learning Objectives

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

    • 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 softwares and packages to conduct time-to-event data analysis
  • Course Description

    The course will introduce fundamental concepts, theory and methods in survival analysis. The emphasis is on statistical tools and model interpretations which are useful in medical follow-up studies and in general time-to-event studies. The content of the course includes hazard functions, survival functions, types of censoring and truncation, Kaplan-Meier estimates, log-rank tests and their generalization. Parametric inference includes likelihood estimation and the exponential, Weibull, log-logistic and other relevant distributions. Statistical methods and theory for the proportional hazard models (Cox model) are discussed in detail, with extensions to time-dependent covariates. Clinical and epidemiological examples included in class presentation and homework illustrate various statistical procedures.


  • Intended Audience
    Biostatistics students and quantitatively-oriented students from other depts
  • Methods of Assessment

    Student evaluation based on problem sets, a quiz and a final exam.

  • Prerequisites

    Biostatistics 140.651 or equivalent. Knowledge of fundamental probability and statistical theory is required.

  • Required Text(s)

    Optional references:

    *Lee, E. “Statistical Methods for Survival Data Analysis”, Wadowrth, 2nd-edition,
    1992.*Scheike and Martinussen. Dynamic Regression Models for Survival Data. Springer
    - Statistics for biology and health.
    *Collett, D. “Modelling Survival Data in Medical Research”, Chapman and Hall,
    **Kleinbaum, DG (1996) Survival Analysis: A Self Learning Text. Springer.
    **Cox, R. and Oakes, D. “Analysis of Suvival Data”, Chapman and Hall, 1984.
    **Kalbfleisch J. D. and Prentice, R. L. “The Statistical Analysis of Failure Time
    Data”, Wiley, 2002.
    *Hosmer D.W., Lemeshow, S. and May S. Applied Survival Analysis: Regression
    Modeling of Time to Event Data. Wiley Series in Probability and Statistics 2008.

    *: Introductory
    **: Intermidiate~Advanced

  • Course Schedule

    Please see the course Session for a full list of dates and items for this course.

    Tu Thur 3:30 - 4:50 PM; Room W3030
    Course website: http : //
    Lecture Instructor: Mei-Cheng Wang ( )
    Lab. Instructors: Yi Lu( );
    Qing Cai ( )
    Cai Lab. (room W2009): Wednesday 1:30 - 2:20 pm
    Lu Lab. (room W3031[Sep 10, Sep 24, Oct 1, Oct 8], W2009[Sep 17], W2015[Oct 15, Oct 22]): Tuesday 1:30 - 2:20 pm
    Cai Office Hour (room E3033): Friday 12:30 - 1:30 pm
    Lu Office Hour (room E3037): Tuesday 2:30 - 3:30 pm
    Wang Office Hour (room E3614): Friday 11:00am - 12:00

  • Academic Ethics Code

    Students enrolled in the Bloomberg School of Public Health of The Johns Hopkins University assume an obligation to conduct themselves in a manner appropriate to the University's mission as an institution of higher education. A student is obligated to refrain from acts which he or she knows, or under the circumstances has reason to know, impair the academic integrity of the University. Violations of academic integrity include, but are not limited to: cheating; plagiarism; knowingly furnishing false information to any agent of the University for inclusion in the academic record; violation of the rights and welfare of animal or human subjects in research; and misconduct as a member of either School or University committees or recognized groups or organizations.

  • Disability Support Services
    If you are a student with a documented disability who requires an academic accommodation, please contact the Office of Student Life Services at 410-955-3034 or via email at