Skip to main content

Statistics for Psychosocial Research: Structural Models

East Baltimore
2nd Term
Academic Year
2023 - 2024
Instruction Method
Class Time(s)
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
Available to Undergraduate
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Qian-Li Xue
Contact Email
Frequency Schedule
Every Year
Next Offered
2024 - 2025

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
This course is evaluated as follows:
  • 33% Participation
  • 33% Problem sets
  • 33% Final Exam
Jointly Offered With
Special Comments

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