140.658.01 | AY 2013-2014 - 2nd Term | 4 Credit(s)
MW 10:30:00 AM
  • Contact Information
    Qian-Li Xue
    Jeannie-Marie Leoutsakos
  • Course Learning Objectives

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

    • design path analysis models
    • analyze latent variable panel data with linear structural equation models
    • design latent class analysis models in the situation of categorical data
    • describe causal inference techniques
  • Course Description
    Presents quantitative approaches to theory construction in the context of multiple response variables, with models for both continuous and categorical data. Topics include the statistical basis for causal inference; principles of path analysis; linear structural equation analysis incorporating measurement models; latent class regression; and analysis of panel data with observed and latent variable models. Draws examples from the social sciences, including the status attainment approach to intergenerational mobility, behavior genetics models of disease and environment, consumer satisfaction, functional impairment and disability, and quality of life.
  • Intended Audience
    Doctoral students interested in Psychosocial Sciences or statistical methodology
  • Methods of Assessment
    Student evaluation based on class participation, problem sets, and a final exam.
  • Prerequisites
    330.657 or consent of instructor
  • Required Text(s)

    Additional Faculty Notes:

    Bollen, KA. Structural Equations with Latent Variables, New York: Wiley and Sons, 1989.

  • Course Schedule

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

  • 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
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