BIOSTATISTICAL ANALYSIS OF EPIDEMIOLOGIC DATA I: LOGISTIC REGRESSION Syllabus

140.676.11 | AY 2013-2014 - Summer Inst. Term | 2 Credit(s)
MTWThF 8:30:00 AM
  • Contact Information
  • Course Learning Objectives

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

    • identify advanced statistical techniques for epidemiologic data
    • utilize model-free methods, illustrated by the 2 by k table and by combining a series of 2 by 2 tables using weighted averages
    • employ estimation and likelihood methods
    • utilize linear logistic analysis methods to explore categorical data
    • list the biostatistical concepts of additivity, independence, confounding, and interaction in the context of logistic models
  • Course Description

    Uses a "workshop" approach to teach advanced statistical techniques for epidemiologic data. Starts with a discussion of model-free methods, illustrated by the 2 by k table, and combining a series of 2 by 2 tables using weighted averages. Reviews estimation and likelihood methods. Discusses linear logistic analysis methods used to explore categorical data. Presents the biostatistical concepts of additivity, independence, confounding, and interaction in the context of logistic models

  • Intended Audience

    JHSPH students and Summer Institute participants

  • Methods of Assessment

    Grading Policy: Final Exam or paper

    Grading Restrictions: Letter grade

  • 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.