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Statistics for Psychosocial Research: Structural Models

East Baltimore
2nd term
4 credits
Academic Year:
2022 - 2023
Instruction Method:
Class Times:
  • M W,  10:30 - 11:50am
Lab Times:
  • Friday,  10:00 - 10:50am (01)
  • Friday,  11:00 - 11:50am (02)
Auditors Allowed:
Yes, with instructor consent
Undergrads Allowed:
Grading Restriction:
Letter Grade or Pass/Fail
Course Instructors:
Qian-Li Xue

330.657 or consent of instructor


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.

Learning Objectives:

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

  1. Design path analysis models
  2. Analyze latent variable panel data with linear structural equation models
  3. Design latent class analysis models in the situation of categorical data
  4. Describe causal inference techniques
Methods of Assessment:

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

Instructor Consent:

Consent required for some students

Consent Note:

330.657 or consent of instructor

For consent, contact:

Jointly Offered With:
Special Comments:

Students must register for one of the computer labs, either 140.958.01 or 140.958.02.