ANALYSIS OF LONGITUDINAL DATA Syllabus

140.608.11 | AY 2013-2014 - Summer Inst. Term | 2 Credit(s)
MTWThF 1:30:00 PM
  • Contact Information
  • Course Learning Objectives

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

    • Prepare graphical or tabular displays of longitudinal data that effectively communicate the patterns of scientific interest
    • Use a general linear model to make scientific inferences about the relationship between response and explanatory variables while accounting for the correlation among repeated responses for an individual
    • Use marginal, random effects, or transitional generalized linear models to make scientific inferences when the repeated observations are binary, counts, or non-Gaussian continuous observations
    • Use SAS or STATA to conduct the appropriate longitudinal data analyses
  • Course Description

    Covers statistical models for drawing scientific inferences from longitudinal data. Topics include longitudinal study design; exploring longitudinal data; linear and generalized linear regression models for correlated data, including marginal, random effects, and transition models; and handling missing data.

  • Intended Audience

    JHSPH students and Summer Institute participants

  • Methods of Assessment

    Grading Policy: Student evaluation based on analysis of a longitudinal data set, presentation of the results, and a written scientific report of the analysis methods and results

    Grading Restrictions: Letter grade

  • Prerequisites

    Intermediate level biostatistics and epidemiology

  • Academic Ethics Code

    The code, discussed in the Policy and Procedure Memorandum for Students, March 31, 2002, will be adhered to in this class:

    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 Betty H. Addison in the Office of Student Life Services: baddison@jhsph.edu, 410-955-3034, or 2017 E. Monument Street.